Overview

Dataset statistics

Number of variables172
Number of observations57
Missing cells1702
Missing cells (%)17.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory76.7 KiB
Average record size in memory1.3 KiB

Variable types

Categorical167
Numeric2
Unsupported3

Alerts

qualdefic has constant value "Física" Constant
orientsex is highly correlated with idgen and 28 other fieldsHigh correlation
idgen is highly correlated with orientsex and 42 other fieldsHigh correlation
intersex is highly correlated with ondmora and 21 other fieldsHigh correlation
raca is highly correlated with escol and 28 other fieldsHigh correlation
idade is highly correlated with tpnaoposse and 33 other fieldsHigh correlation
ondmora is highly correlated with orientsex and 70 other fieldsHigh correlation
defic is highly correlated with tpnaoposse and 18 other fieldsHigh correlation
escol is highly correlated with orientsex and 47 other fieldsHigh correlation
posdoc is highly correlated with tpnaoposse and 35 other fieldsHigh correlation
possedoc is highly correlated with eletrcs and 11 other fieldsHigh correlation
tpnaoposse is highly correlated with orientsex and 115 other fieldsHigh correlation
ufnasc is highly correlated with raca and 31 other fieldsHigh correlation
retifsoc is highly correlated with orientsex and 32 other fieldsHigh correlation
retifgrat is highly correlated with orientsex and 35 other fieldsHigh correlation
relacamor is highly correlated with idgen and 11 other fieldsHigh correlation
qtdmora is highly correlated with orientsex and 30 other fieldsHigh correlation
grpmora is highly correlated with orientsex and 23 other fieldsHigh correlation
famidgen is highly correlated with tpnaoposse and 15 other fieldsHigh correlation
ididgen is highly correlated with idade and 37 other fieldsHigh correlation
famreac is highly correlated with idgen and 85 other fieldsHigh correlation
relafam is highly correlated with ondmora and 25 other fieldsHigh correlation
respons is highly correlated with posdoc and 21 other fieldsHigh correlation
violdom is highly correlated with ondmora and 25 other fieldsHigh correlation
alclfam is highly correlated with defic and 22 other fieldsHigh correlation
filho is highly correlated with idgen and 30 other fieldsHigh correlation
contrcs is highly correlated with defic and 31 other fieldsHigh correlation
saneam is highly correlated with orientsex and 54 other fieldsHigh correlation
proprcs is highly correlated with intersex and 33 other fieldsHigh correlation
eletrcs is highly correlated with idade and 111 other fieldsHigh correlation
dormecs is highly correlated with posdoc and 17 other fieldsHigh correlation
comunservs is highly correlated with orientsex and 72 other fieldsHigh correlation
vias is highly correlated with tpnaoposse and 25 other fieldsHigh correlation
espcscomn is highly correlated with orientsex and 118 other fieldsHigh correlation
cartass is highly correlated with idade and 10 other fieldsHigh correlation
empatual is highly correlated with posdoc and 22 other fieldsHigh correlation
trabcomn is highly correlated with idade and 20 other fieldsHigh correlation
profs is highly correlated with orientsex and 93 other fieldsHigh correlation
profsex is highly correlated with orientsex and 31 other fieldsHigh correlation
renda is highly correlated with ondmora and 15 other fieldsHigh correlation
depndfam is highly correlated with ondmora and 28 other fieldsHigh correlation
usomei is highly correlated with ondmora and 20 other fieldsHigh correlation
nomesoctrb is highly correlated with tpnaoposse and 14 other fieldsHigh correlation
pqnaousanm is highly correlated with idgen and 52 other fieldsHigh correlation
assdtrb is highly correlated with orientsex and 39 other fieldsHigh correlation
discrsectrb is highly correlated with orientsex and 31 other fieldsHigh correlation
discractrb is highly correlated with idgen and 32 other fieldsHigh correlation
bolsafam is highly correlated with possedoc and 14 other fieldsHigh correlation
ctbolsafam is highly correlated with famreac and 14 other fieldsHigh correlation
demisidgen is highly correlated with defic and 32 other fieldsHigh correlation
dempand is highly correlated with idgen and 16 other fieldsHigh correlation
auxemerg is highly correlated with ondmora and 29 other fieldsHigh correlation
estud is highly correlated with idgen and 22 other fieldsHigh correlation
tpinstitu is highly correlated with idgen and 17 other fieldsHigh correlation
matergrts is highly correlated with ondmora and 18 other fieldsHigh correlation
instiloc is highly correlated with idgen and 31 other fieldsHigh correlation
mobinsti is highly correlated with orientsex and 54 other fieldsHigh correlation
pandestd is highly correlated with orientsex and 50 other fieldsHigh correlation
desisest is highly correlated with ondmora and 63 other fieldsHigh correlation
discrescol is highly correlated with idade and 12 other fieldsHigh correlation
tpdiscr is highly correlated with intersex and 63 other fieldsHigh correlation
violescol is highly correlated with tpnaoposse and 30 other fieldsHigh correlation
quemviolescol is highly correlated with raca and 36 other fieldsHigh correlation
nmsocescol is highly correlated with idgen and 26 other fieldsHigh correlation
acdscrmnscl is highly correlated with ondmora and 38 other fieldsHigh correlation
profn is highly correlated with escol and 25 other fieldsHigh correlation
profq is highly correlated with ondmora and 21 other fieldsHigh correlation
proft is highly correlated with ondmora and 18 other fieldsHigh correlation
usaprep is highly correlated with idgen and 24 other fieldsHigh correlation
pqprep is highly correlated with tpnaoposse and 9 other fieldsHigh correlation
medcontr is highly correlated with raca and 29 other fieldsHigh correlation
medhiv is highly correlated with idade and 17 other fieldsHigh correlation
pilseg is highly correlated with orientsex and 59 other fieldsHigh correlation
freqmed is highly correlated with idgen and 33 other fieldsHigh correlation
freqdent is highly correlated with ondmora and 15 other fieldsHigh correlation
exhiv is highly correlated with ondmora and 16 other fieldsHigh correlation
reshiv is highly correlated with ondmora and 20 other fieldsHigh correlation
exsif is highly correlated with escol and 34 other fieldsHigh correlation
ressif is highly correlated with saneam and 18 other fieldsHigh correlation
exhep is highly correlated with tpnaoposse and 13 other fieldsHigh correlation
reshep is highly correlated with ondmora and 23 other fieldsHigh correlation
exist is highly correlated with tpnaoposse and 26 other fieldsHigh correlation
resist is highly correlated with qtdmora and 14 other fieldsHigh correlation
hormo is highly correlated with idgen and 23 other fieldsHigh correlation
fimhormo is highly correlated with ondmora and 34 other fieldsHigh correlation
medprehorm is highly correlated with ididgen and 27 other fieldsHigh correlation
silic is highly correlated with idgen and 12 other fieldsHigh correlation
fumo is highly correlated with escol and 21 other fieldsHigh correlation
frequs is highly correlated with eletrcs and 7 other fieldsHigh correlation
usotox is highly correlated with raca and 42 other fieldsHigh correlation
motnfrequs is highly correlated with intersex and 53 other fieldsHigh correlation
assistpsi is highly correlated with intersex and 24 other fieldsHigh correlation
servpsi is highly correlated with ondmora and 25 other fieldsHigh correlation
servsoc is highly correlated with tpnaoposse and 17 other fieldsHigh correlation
medcserv is highly correlated with tpnaoposse and 18 other fieldsHigh correlation
vaccovid is highly correlated with defic and 19 other fieldsHigh correlation
vacvida is highly correlated with orientsex and 88 other fieldsHigh correlation
plansaude is highly correlated with raca and 27 other fieldsHigh correlation
disttranst is highly correlated with intersex and 34 other fieldsHigh correlation
alimen is highly correlated with tpnaoposse and 24 other fieldsHigh correlation
expohiv is highly correlated with defic and 25 other fieldsHigh correlation
servcsf is highly correlated with tpnaoposse and 17 other fieldsHigh correlation
naocsf is highly correlated with orientsex and 35 other fieldsHigh correlation
posicovid is highly correlated with saneam and 19 other fieldsHigh correlation
quadcovid is highly correlated with famreac and 30 other fieldsHigh correlation
prcccovid is highly correlated with ondmora and 47 other fieldsHigh correlation
violmed is highly correlated with tpnaoposse and 21 other fieldsHigh correlation
tpviolmed is highly correlated with raca and 67 other fieldsHigh correlation
agrsidgen is highly correlated with idade and 23 other fieldsHigh correlation
ondeagres is highly correlated with orientsex and 108 other fieldsHigh correlation
usobanh is highly correlated with tpnaoposse and 11 other fieldsHigh correlation
ondeocor is highly correlated with orientsex and 129 other fieldsHigh correlation
violsex is highly correlated with orientsex and 34 other fieldsHigh correlation
ondviolsex is highly correlated with orientsex and 70 other fieldsHigh correlation
expidgen is highly correlated with filho and 25 other fieldsHigh correlation
centrolgbti is highly correlated with ondmora and 18 other fieldsHigh correlation
violverb is highly correlated with ondmora and 27 other fieldsHigh correlation
piadidgen is highly correlated with tpnaoposse and 27 other fieldsHigh correlation
idgenexpo is highly correlated with ondmora and 21 other fieldsHigh correlation
usocentr is highly correlated with ondmora and 18 other fieldsHigh correlation
motnaocentr is highly correlated with ondmora and 41 other fieldsHigh correlation
agresstp is highly correlated with idgen and 100 other fieldsHigh correlation
classagrs is highly correlated with idgen and 83 other fieldsHigh correlation
racaagres is highly correlated with idgen and 78 other fieldsHigh correlation
abrdg is highly correlated with tpnaoposse and 21 other fieldsHigh correlation
ttoidgen is highly correlated with orientsex and 49 other fieldsHigh correlation
ameaidgen is highly correlated with escol and 37 other fieldsHigh correlation
delegc is highly correlated with idgen and 16 other fieldsHigh correlation
ondeplc is highly correlated with orientsex and 70 other fieldsHigh correlation
acuspol is highly correlated with idade and 29 other fieldsHigh correlation
violplc is highly correlated with raca and 40 other fieldsHigh correlation
extorsplc is highly correlated with ondmora and 21 other fieldsHigh correlation
foraplc is highly correlated with idade and 11 other fieldsHigh correlation
moraplc is highly correlated with idgen and 27 other fieldsHigh correlation
invcsplc is highly correlated with tpnaoposse and 18 other fieldsHigh correlation
vldenunplc is highly correlated with defic and 29 other fieldsHigh correlation
possuireli is highly correlated with ondmora and 9 other fieldsHigh correlation
tprelig is highly correlated with idgen and 107 other fieldsHigh correlation
criareli is highly correlated with idgen and 80 other fieldsHigh correlation
proxreli is highly correlated with tpnaoposse and 17 other fieldsHigh correlation
opressreli is highly correlated with ondmora and 20 other fieldsHigh correlation
violreli is highly correlated with ondmora and 25 other fieldsHigh correlation
orisexreli is highly correlated with idgen and 18 other fieldsHigh correlation
desacrerreli is highly correlated with discrsectrb and 12 other fieldsHigh correlation
forcareli is highly correlated with grpmora and 43 other fieldsHigh correlation
igrevive is highly correlated with intersex and 22 other fieldsHigh correlation
acesnet is highly correlated with intersex and 93 other fieldsHigh correlation
perfap is highly correlated with idade and 11 other fieldsHigh correlation
topuso is highly correlated with orientsex and 75 other fieldsHigh correlation
usopara is highly correlated with idgen and 100 other fieldsHigh correlation
sitweb is highly correlated with orientsex and 94 other fieldsHigh correlation
continvs is highly correlated with idgen and 68 other fieldsHigh correlation
netservpub is highly correlated with ondmora and 26 other fieldsHigh correlation
tpnetserv is highly correlated with idgen and 99 other fieldsHigh correlation
difserv is highly correlated with orientsex and 77 other fieldsHigh correlation
cadbio is highly correlated with ondmora and 16 other fieldsHigh correlation
confbio is highly correlated with tpnaoposse and 17 other fieldsHigh correlation
cinema is highly correlated with ondmora and 30 other fieldsHigh correlation
museus is highly correlated with eletrcs and 13 other fieldsHigh correlation
biblio is highly correlated with ondmora and 14 other fieldsHigh correlation
ler is highly correlated with tpnaoposse and 20 other fieldsHigh correlation
bailes is highly correlated with idade and 15 other fieldsHigh correlation
eventos is highly correlated with espcscomn and 9 other fieldsHigh correlation
desloc is highly correlated with raca and 38 other fieldsHigh correlation
evenpub is highly correlated with posdoc and 14 other fieldsHigh correlation
apcult is highly correlated with idgen and 18 other fieldsHigh correlation
projpub is highly correlated with raca and 31 other fieldsHigh correlation
projart is highly correlated with posdoc and 18 other fieldsHigh correlation
inters is highly correlated with raca and 81 other fieldsHigh correlation
orientsex has 1 (1.8%) missing values Missing
idgen has 1 (1.8%) missing values Missing
intersex has 1 (1.8%) missing values Missing
idade has 1 (1.8%) missing values Missing
qualdefic has 55 (96.5%) missing values Missing
possedoc has 1 (1.8%) missing values Missing
tpnaoposse has 49 (86.0%) missing values Missing
motvimigr has 57 (100.0%) missing values Missing
retifgrat has 47 (82.5%) missing values Missing
qtdmora has 3 (5.3%) missing values Missing
grpmora has 24 (42.1%) missing values Missing
famidgen has 3 (5.3%) missing values Missing
ididgen has 5 (8.8%) missing values Missing
famreac has 4 (7.0%) missing values Missing
relafam has 3 (5.3%) missing values Missing
respons has 3 (5.3%) missing values Missing
violdom has 3 (5.3%) missing values Missing
alclfam has 3 (5.3%) missing values Missing
filho has 4 (7.0%) missing values Missing
contrcs has 3 (5.3%) missing values Missing
equiprua has 57 (100.0%) missing values Missing
saneam has 3 (5.3%) missing values Missing
proprcs has 3 (5.3%) missing values Missing
eletrcs has 3 (5.3%) missing values Missing
dormecs has 4 (7.0%) missing values Missing
comunservs has 3 (5.3%) missing values Missing
vias has 3 (5.3%) missing values Missing
espcscomn has 4 (7.0%) missing values Missing
cartass has 3 (5.3%) missing values Missing
empatual has 3 (5.3%) missing values Missing
trabcomn has 13 (22.8%) missing values Missing
profs has 9 (15.8%) missing values Missing
profsex has 7 (12.3%) missing values Missing
renda has 8 (14.0%) missing values Missing
depndfam has 7 (12.3%) missing values Missing
usomei has 12 (21.1%) missing values Missing
nomesoctrb has 8 (14.0%) missing values Missing
pqnaousanm has 43 (75.4%) missing values Missing
assdtrb has 8 (14.0%) missing values Missing
discrsectrb has 8 (14.0%) missing values Missing
discractrb has 8 (14.0%) missing values Missing
bolsafam has 7 (12.3%) missing values Missing
ctbolsafam has 8 (14.0%) missing values Missing
demisidgen has 8 (14.0%) missing values Missing
dempand has 10 (17.5%) missing values Missing
auxemerg has 7 (12.3%) missing values Missing
estud has 3 (5.3%) missing values Missing
tpinstitu has 3 (5.3%) missing values Missing
matergrts has 3 (5.3%) missing values Missing
instiloc has 3 (5.3%) missing values Missing
mobinsti has 43 (75.4%) missing values Missing
pandestd has 43 (75.4%) missing values Missing
desisest has 40 (70.2%) missing values Missing
discrescol has 3 (5.3%) missing values Missing
tpdiscr has 20 (35.1%) missing values Missing
violescol has 3 (5.3%) missing values Missing
quemviolescol has 13 (22.8%) missing values Missing
nmsocescol has 43 (75.4%) missing values Missing
acdscrmnscl has 42 (73.7%) missing values Missing
profn has 3 (5.3%) missing values Missing
profq has 3 (5.3%) missing values Missing
proft has 3 (5.3%) missing values Missing
usaprep has 4 (7.0%) missing values Missing
pqprep has 3 (5.3%) missing values Missing
medcontr has 3 (5.3%) missing values Missing
medhiv has 3 (5.3%) missing values Missing
pilseg has 47 (82.5%) missing values Missing
freqmed has 3 (5.3%) missing values Missing
freqdent has 3 (5.3%) missing values Missing
exhiv has 3 (5.3%) missing values Missing
reshiv has 13 (22.8%) missing values Missing
exsif has 3 (5.3%) missing values Missing
ressif has 16 (28.1%) missing values Missing
exhep has 3 (5.3%) missing values Missing
reshep has 20 (35.1%) missing values Missing
exist has 3 (5.3%) missing values Missing
resist has 31 (54.4%) missing values Missing
hormo has 3 (5.3%) missing values Missing
fimhormo has 37 (64.9%) missing values Missing
medprehorm has 37 (64.9%) missing values Missing
silic has 3 (5.3%) missing values Missing
fumo has 3 (5.3%) missing values Missing
frequs has 3 (5.3%) missing values Missing
usotox has 3 (5.3%) missing values Missing
motnfrequs has 42 (73.7%) missing values Missing
assistpsi has 3 (5.3%) missing values Missing
servpsi has 3 (5.3%) missing values Missing
servsoc has 3 (5.3%) missing values Missing
medcserv has 3 (5.3%) missing values Missing
vaccovid has 4 (7.0%) missing values Missing
vacvida has 3 (5.3%) missing values Missing
plansaude has 4 (7.0%) missing values Missing
disttranst has 3 (5.3%) missing values Missing
alimen has 3 (5.3%) missing values Missing
expohiv has 6 (10.5%) missing values Missing
servcsf has 3 (5.3%) missing values Missing
naocsf has 36 (63.2%) missing values Missing
posicovid has 3 (5.3%) missing values Missing
quadcovid has 47 (82.5%) missing values Missing
prcccovid has 3 (5.3%) missing values Missing
violmed has 3 (5.3%) missing values Missing
tpviolmed has 40 (70.2%) missing values Missing
agrsidgen has 3 (5.3%) missing values Missing
ondeagres has 32 (56.1%) missing values Missing
usobanh has 3 (5.3%) missing values Missing
ondeocor has 43 (75.4%) missing values Missing
violsex has 4 (7.0%) missing values Missing
ondviolsex has 33 (57.9%) missing values Missing
expidgen has 3 (5.3%) missing values Missing
centrolgbti has 3 (5.3%) missing values Missing
violverb has 3 (5.3%) missing values Missing
piadidgen has 3 (5.3%) missing values Missing
idgenexpo has 3 (5.3%) missing values Missing
usocentr has 3 (5.3%) missing values Missing
motnaocentr has 17 (29.8%) missing values Missing
agresstp has 9 (15.8%) missing values Missing
classagrs has 9 (15.8%) missing values Missing
racaagres has 7 (12.3%) missing values Missing
ttoidgen has 16 (28.1%) missing values Missing
ameaidgen has 15 (26.3%) missing values Missing
delegc has 14 (24.6%) missing values Missing
ondeplc has 15 (26.3%) missing values Missing
acuspol has 14 (24.6%) missing values Missing
violplc has 15 (26.3%) missing values Missing
foraplc has 1 (1.8%) missing values Missing
vldenunplc has 1 (1.8%) missing values Missing
tprelig has 20 (35.1%) missing values Missing
criareli has 1 (1.8%) missing values Missing
orisexreli has 1 (1.8%) missing values Missing
forcareli has 1 (1.8%) missing values Missing
topuso has 2 (3.5%) missing values Missing
usopara has 3 (5.3%) missing values Missing
sitweb has 4 (7.0%) missing values Missing
continvs has 5 (8.8%) missing values Missing
tpnetserv has 24 (42.1%) missing values Missing
difserv has 24 (42.1%) missing values Missing
confbio has 1 (1.8%) missing values Missing
desloc has 30 (52.6%) missing values Missing
projpub has 1 (1.8%) missing values Missing
inters has 1 (1.8%) missing values Missing
progress has 57 (100.0%) missing values Missing
espcscomn is uniformly distributed Uniform
acdscrmnscl is uniformly distributed Uniform
ondeocor is uniformly distributed Uniform
agresstp is uniformly distributed Uniform
usopara is uniformly distributed Uniform
motvimigr is an unsupported type, check if it needs cleaning or further analysis Unsupported
equiprua is an unsupported type, check if it needs cleaning or further analysis Unsupported
progress is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2022-05-31 18:03:26.581145
Analysis finished2022-05-31 18:05:20.316763
Duration1 minute and 53.74 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

orientsex
Categorical

HIGH CORRELATION
MISSING

Distinct7
Distinct (%)12.5%
Missing1
Missing (%)1.8%
Memory size584.0 B
Heterossexual
23 
Bissexual
11 
Gay/ Bicha
11 
Lésbica/ Sapatão
Homossexual
Other values (2)

Length

Max length21
Median length16
Mean length11.78571429
Min length9

Characters and Unicode

Total characters660
Distinct characters31
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.8%

Sample

1st rowBissexual
2nd rowHeterossexual
3rd rowBissexual
4th rowHeterossexual
5th rowHeterossexual

Common Values

ValueCountFrequency (%)
Heterossexual23
40.4%
Bissexual11
19.3%
Gay/ Bicha11
19.3%
Lésbica/ Sapatão5
 
8.8%
Homossexual3
 
5.3%
Pansexual2
 
3.5%
Nenhuma dessas opções1
 
1.8%
(Missing)1
 
1.8%

Length

2022-05-31T15:05:20.485888image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:20.649407image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
heterossexual23
31.1%
bissexual11
14.9%
gay11
14.9%
bicha11
14.9%
lésbica5
 
6.8%
sapatão5
 
6.8%
homossexual3
 
4.1%
pansexual2
 
2.7%
nenhuma1
 
1.4%
dessas1
 
1.4%

Most occurring characters

ValueCountFrequency (%)
e88
13.3%
s85
12.9%
a80
12.1%
u40
 
6.1%
x39
 
5.9%
l39
 
5.9%
o35
 
5.3%
t28
 
4.2%
i27
 
4.1%
H26
 
3.9%
Other values (21)173
26.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter554
83.9%
Uppercase Letter72
 
10.9%
Space Separator18
 
2.7%
Other Punctuation16
 
2.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e88
15.9%
s85
15.3%
a80
14.4%
u40
7.2%
x39
7.0%
l39
7.0%
o35
 
6.3%
t28
 
5.1%
i27
 
4.9%
r23
 
4.2%
Other values (12)70
12.6%
Uppercase Letter
ValueCountFrequency (%)
H26
36.1%
B22
30.6%
G11
15.3%
S5
 
6.9%
L5
 
6.9%
P2
 
2.8%
N1
 
1.4%
Space Separator
ValueCountFrequency (%)
18
100.0%
Other Punctuation
ValueCountFrequency (%)
/16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin626
94.8%
Common34
 
5.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e88
14.1%
s85
13.6%
a80
12.8%
u40
 
6.4%
x39
 
6.2%
l39
 
6.2%
o35
 
5.6%
t28
 
4.5%
i27
 
4.3%
H26
 
4.2%
Other values (19)139
22.2%
Common
ValueCountFrequency (%)
18
52.9%
/16
47.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII648
98.2%
None12
 
1.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e88
13.6%
s85
13.1%
a80
12.3%
u40
 
6.2%
x39
 
6.0%
l39
 
6.0%
o35
 
5.4%
t28
 
4.3%
i27
 
4.2%
H26
 
4.0%
Other values (17)161
24.8%
None
ValueCountFrequency (%)
é5
41.7%
ã5
41.7%
ç1
 
8.3%
õ1
 
8.3%

idgen
Categorical

HIGH CORRELATION
MISSING

Distinct8
Distinct (%)14.3%
Missing1
Missing (%)1.8%
Memory size584.0 B
Mulher trans
21 
Travesti
11 
Homem Cisgênero
10 
Mulher Cisgênera
Nenhuma
 
2
Other values (3)

Length

Max length16
Median length15
Mean length12
Min length7

Characters and Unicode

Total characters672
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)3.6%

Sample

1st rowNenhuma
2nd rowTravesti
3rd rowTravesti
4th rowMulher trans
5th rowMulher trans

Common Values

ValueCountFrequency (%)
Mulher trans21
36.8%
Travesti11
19.3%
Homem Cisgênero10
17.5%
Mulher Cisgênera8
 
14.0%
Nenhuma2
 
3.5%
Homem trans2
 
3.5%
Outro/a1
 
1.8%
Não binária1
 
1.8%
(Missing)1
 
1.8%

Length

2022-05-31T15:05:20.796049image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:20.934644image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
mulher29
29.6%
trans23
23.5%
homem12
12.2%
travesti11
 
11.2%
cisgênero10
 
10.2%
cisgênera8
 
8.2%
nenhuma2
 
2.0%
outro/a1
 
1.0%
não1
 
1.0%
binária1
 
1.0%

Most occurring characters

ValueCountFrequency (%)
r83
12.4%
e72
 
10.7%
s52
 
7.7%
a46
 
6.8%
n44
 
6.5%
42
 
6.2%
t35
 
5.2%
u32
 
4.8%
i31
 
4.6%
h31
 
4.6%
Other values (16)204
30.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter555
82.6%
Uppercase Letter74
 
11.0%
Space Separator42
 
6.2%
Other Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r83
15.0%
e72
13.0%
s52
9.4%
a46
8.3%
n44
7.9%
t35
 
6.3%
u32
 
5.8%
i31
 
5.6%
h31
 
5.6%
l29
 
5.2%
Other values (8)100
18.0%
Uppercase Letter
ValueCountFrequency (%)
M29
39.2%
C18
24.3%
H12
16.2%
T11
 
14.9%
N3
 
4.1%
O1
 
1.4%
Space Separator
ValueCountFrequency (%)
42
100.0%
Other Punctuation
ValueCountFrequency (%)
/1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin629
93.6%
Common43
 
6.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
r83
13.2%
e72
11.4%
s52
 
8.3%
a46
 
7.3%
n44
 
7.0%
t35
 
5.6%
u32
 
5.1%
i31
 
4.9%
h31
 
4.9%
M29
 
4.6%
Other values (14)174
27.7%
Common
ValueCountFrequency (%)
42
97.7%
/1
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII652
97.0%
None20
 
3.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r83
12.7%
e72
 
11.0%
s52
 
8.0%
a46
 
7.1%
n44
 
6.7%
42
 
6.4%
t35
 
5.4%
u32
 
4.9%
i31
 
4.8%
h31
 
4.8%
Other values (13)184
28.2%
None
ValueCountFrequency (%)
ê18
90.0%
ã1
 
5.0%
á1
 
5.0%

intersex
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)3.6%
Missing1
Missing (%)1.8%
Memory size584.0 B
Não
50 
Sim

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters168
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão
2nd rowNão
3rd rowNão
4th rowNão
5th rowNão

Common Values

ValueCountFrequency (%)
Não50
87.7%
Sim6
 
10.5%
(Missing)1
 
1.8%

Length

2022-05-31T15:05:21.072316image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:21.175996image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não50
89.3%
sim6
 
10.7%

Most occurring characters

ValueCountFrequency (%)
N50
29.8%
ã50
29.8%
o50
29.8%
S6
 
3.6%
i6
 
3.6%
m6
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter112
66.7%
Uppercase Letter56
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
ã50
44.6%
o50
44.6%
i6
 
5.4%
m6
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
N50
89.3%
S6
 
10.7%

Most occurring scripts

ValueCountFrequency (%)
Latin168
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N50
29.8%
ã50
29.8%
o50
29.8%
S6
 
3.6%
i6
 
3.6%
m6
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII118
70.2%
None50
29.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N50
42.4%
o50
42.4%
S6
 
5.1%
i6
 
5.1%
m6
 
5.1%
None
ValueCountFrequency (%)
ã50
100.0%

raca
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size584.0 B
Negra
49 
Branca
Indígena
 
2

Length

Max length8
Median length5
Mean length5.210526316
Min length5

Characters and Unicode

Total characters297
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNegra
2nd rowNegra
3rd rowNegra
4th rowNegra
5th rowNegra

Common Values

ValueCountFrequency (%)
Negra49
86.0%
Branca6
 
10.5%
Indígena2
 
3.5%

Length

2022-05-31T15:05:21.274733image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:21.400398image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
negra49
86.0%
branca6
 
10.5%
indígena2
 
3.5%

Most occurring characters

ValueCountFrequency (%)
a63
21.2%
r55
18.5%
e51
17.2%
g51
17.2%
N49
16.5%
n10
 
3.4%
B6
 
2.0%
c6
 
2.0%
I2
 
0.7%
d2
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter240
80.8%
Uppercase Letter57
 
19.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a63
26.2%
r55
22.9%
e51
21.2%
g51
21.2%
n10
 
4.2%
c6
 
2.5%
d2
 
0.8%
í2
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
N49
86.0%
B6
 
10.5%
I2
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
Latin297
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a63
21.2%
r55
18.5%
e51
17.2%
g51
17.2%
N49
16.5%
n10
 
3.4%
B6
 
2.0%
c6
 
2.0%
I2
 
0.7%
d2
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII295
99.3%
None2
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a63
21.4%
r55
18.6%
e51
17.3%
g51
17.3%
N49
16.6%
n10
 
3.4%
B6
 
2.0%
c6
 
2.0%
I2
 
0.7%
d2
 
0.7%
None
ValueCountFrequency (%)
í2
100.0%

idade
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct26
Distinct (%)46.4%
Missing1
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean29.58928571
Minimum18
Maximum54
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size584.0 B
2022-05-31T15:05:21.508109image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile19
Q123
median27.5
Q334.5
95-th percentile45.75
Maximum54
Range36
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation8.591278423
Coefficient of variation (CV)0.2903509907
Kurtosis0.6997354727
Mean29.58928571
Median Absolute Deviation (MAD)5.5
Skewness1.030378768
Sum1657
Variance73.81006494
MonotonicityNot monotonic
2022-05-31T15:05:21.623799image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
235
 
8.8%
224
 
7.0%
264
 
7.0%
284
 
7.0%
364
 
7.0%
213
 
5.3%
273
 
5.3%
343
 
5.3%
193
 
5.3%
382
 
3.5%
Other values (16)21
36.8%
ValueCountFrequency (%)
181
 
1.8%
193
5.3%
201
 
1.8%
213
5.3%
224
7.0%
235
8.8%
242
 
3.5%
252
 
3.5%
264
7.0%
273
5.3%
ValueCountFrequency (%)
541
 
1.8%
531
 
1.8%
481
 
1.8%
452
3.5%
411
 
1.8%
401
 
1.8%
382
3.5%
371
 
1.8%
364
7.0%
343
5.3%

ondmora
Categorical

HIGH CORRELATION

Distinct20
Distinct (%)35.1%
Missing0
Missing (%)0.0%
Memory size584.0 B
Maré
15 
Palmares
Rocinha
Vila Cruzeiro
Não moro em comunidade
Other values (15)
15 

Length

Max length41
Median length27
Mean length10.33333333
Min length4

Characters and Unicode

Total characters589
Distinct characters48
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)26.3%

Sample

1st rowNão moro em comunidade
2nd rowNão moro em comunidade
3rd rowRocinha
4th rowRocinha
5th rowRocinha

Common Values

ValueCountFrequency (%)
Maré15
26.3%
Palmares9
15.8%
Rocinha8
14.0%
Vila Cruzeiro7
12.3%
Não moro em comunidade3
 
5.3%
Ceilândia - DF1
 
1.8%
Favela da Carobinha, Campo Grande (ZO-RJ)1
 
1.8%
Vila Kennedy 1
 
1.8%
Vila Kennedy1
 
1.8%
ramos1
 
1.8%
Other values (10)10
17.5%

Length

2022-05-31T15:05:21.761474image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
maré15
15.6%
vila9
 
9.4%
palmares9
 
9.4%
rocinha8
 
8.3%
cruzeiro7
 
7.3%
não3
 
3.1%
moro3
 
3.1%
em3
 
3.1%
comunidade3
 
3.1%
kennedy2
 
2.1%
Other values (32)34
35.4%

Most occurring characters

ValueCountFrequency (%)
a81
13.8%
r57
 
9.7%
o45
 
7.6%
42
 
7.1%
e41
 
7.0%
i39
 
6.6%
n29
 
4.9%
l22
 
3.7%
m22
 
3.7%
u18
 
3.1%
Other values (38)193
32.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter459
77.9%
Uppercase Letter81
 
13.8%
Space Separator42
 
7.1%
Dash Punctuation3
 
0.5%
Other Punctuation2
 
0.3%
Close Punctuation1
 
0.2%
Open Punctuation1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a81
17.6%
r57
12.4%
o45
9.8%
e41
8.9%
i39
8.5%
n29
 
6.3%
l22
 
4.8%
m22
 
4.8%
u18
 
3.9%
d17
 
3.7%
Other values (16)88
19.2%
Uppercase Letter
ValueCountFrequency (%)
M17
21.0%
C16
19.8%
P11
13.6%
R10
12.3%
V9
11.1%
F3
 
3.7%
N3
 
3.7%
D2
 
2.5%
J2
 
2.5%
K2
 
2.5%
Other values (6)6
 
7.4%
Other Punctuation
ValueCountFrequency (%)
/1
50.0%
,1
50.0%
Space Separator
ValueCountFrequency (%)
42
100.0%
Dash Punctuation
ValueCountFrequency (%)
-3
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin540
91.7%
Common49
 
8.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a81
15.0%
r57
 
10.6%
o45
 
8.3%
e41
 
7.6%
i39
 
7.2%
n29
 
5.4%
l22
 
4.1%
m22
 
4.1%
u18
 
3.3%
d17
 
3.1%
Other values (32)169
31.3%
Common
ValueCountFrequency (%)
42
85.7%
-3
 
6.1%
/1
 
2.0%
)1
 
2.0%
(1
 
2.0%
,1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII569
96.6%
None20
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a81
14.2%
r57
 
10.0%
o45
 
7.9%
42
 
7.4%
e41
 
7.2%
i39
 
6.9%
n29
 
5.1%
l22
 
3.9%
m22
 
3.9%
u18
 
3.2%
Other values (35)173
30.4%
None
ValueCountFrequency (%)
é15
75.0%
ã4
 
20.0%
â1
 
5.0%

defic
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size584.0 B
Não
54 
Sim
 
2
Não tenho certeza
 
1

Length

Max length17
Median length3
Mean length3.245614035
Min length3

Characters and Unicode

Total characters185
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.8%

Sample

1st rowNão
2nd rowNão
3rd rowNão
4th rowNão tenho certeza
5th rowNão

Common Values

ValueCountFrequency (%)
Não54
94.7%
Sim2
 
3.5%
Não tenho certeza1
 
1.8%

Length

2022-05-31T15:05:21.911031image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:22.031707image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não55
93.2%
sim2
 
3.4%
tenho1
 
1.7%
certeza1
 
1.7%

Most occurring characters

ValueCountFrequency (%)
o56
30.3%
N55
29.7%
ã55
29.7%
e3
 
1.6%
S2
 
1.1%
i2
 
1.1%
m2
 
1.1%
2
 
1.1%
t2
 
1.1%
n1
 
0.5%
Other values (5)5
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter126
68.1%
Uppercase Letter57
30.8%
Space Separator2
 
1.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o56
44.4%
ã55
43.7%
e3
 
2.4%
i2
 
1.6%
m2
 
1.6%
t2
 
1.6%
n1
 
0.8%
h1
 
0.8%
c1
 
0.8%
r1
 
0.8%
Other values (2)2
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
N55
96.5%
S2
 
3.5%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin183
98.9%
Common2
 
1.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o56
30.6%
N55
30.1%
ã55
30.1%
e3
 
1.6%
S2
 
1.1%
i2
 
1.1%
m2
 
1.1%
t2
 
1.1%
n1
 
0.5%
h1
 
0.5%
Other values (4)4
 
2.2%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII130
70.3%
None55
29.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o56
43.1%
N55
42.3%
e3
 
2.3%
S2
 
1.5%
i2
 
1.5%
m2
 
1.5%
2
 
1.5%
t2
 
1.5%
n1
 
0.8%
h1
 
0.8%
Other values (4)4
 
3.1%
None
ValueCountFrequency (%)
ã55
100.0%

qualdefic
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)50.0%
Missing55
Missing (%)96.5%
Memory size584.0 B
Física

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters12
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFísica
2nd rowFísica

Common Values

ValueCountFrequency (%)
Física2
 
3.5%
(Missing)55
96.5%

Length

2022-05-31T15:05:22.134433image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:22.247131image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
física2
100.0%

Most occurring characters

ValueCountFrequency (%)
F2
16.7%
í2
16.7%
s2
16.7%
i2
16.7%
c2
16.7%
a2
16.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter10
83.3%
Uppercase Letter2
 
16.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
í2
20.0%
s2
20.0%
i2
20.0%
c2
20.0%
a2
20.0%
Uppercase Letter
ValueCountFrequency (%)
F2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin12
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
F2
16.7%
í2
16.7%
s2
16.7%
i2
16.7%
c2
16.7%
a2
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII10
83.3%
None2
 
16.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
F2
20.0%
s2
20.0%
i2
20.0%
c2
20.0%
a2
20.0%
None
ValueCountFrequency (%)
í2
100.0%

escol
Categorical

HIGH CORRELATION

Distinct10
Distinct (%)17.5%
Missing0
Missing (%)0.0%
Memory size584.0 B
Ensino médio completo
18 
Ensino médio incompleto
13 
Ensino superior incompleto
Ensino fundamental incompleto
Ensino superior completo
Other values (5)

Length

Max length44
Median length29
Mean length24.33333333
Min length21

Characters and Unicode

Total characters1387
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)5.3%

Sample

1st rowEnsino superior incompleto
2nd rowEnsino superior incompleto
3rd rowCursos profissionalizantes ou de capacitação
4th rowEnsino fundamental incompleto
5th rowEnsino médio completo

Common Values

ValueCountFrequency (%)
Ensino médio completo18
31.6%
Ensino médio incompleto13
22.8%
Ensino superior incompleto7
 
12.3%
Ensino fundamental incompleto6
 
10.5%
Ensino superior completo6
 
10.5%
Pós-graduação incompleta2
 
3.5%
Ensino fundamental completo2
 
3.5%
Cursos profissionalizantes ou de capacitação1
 
1.8%
Ensino médio técnico completo1
 
1.8%
Pós-graduação completa1
 
1.8%

Length

2022-05-31T15:05:22.376821image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:22.533409image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
ensino53
31.0%
médio32
18.7%
completo27
15.8%
incompleto26
15.2%
superior13
 
7.6%
fundamental8
 
4.7%
pós-graduação3
 
1.8%
incompleta2
 
1.2%
cursos1
 
0.6%
profissionalizantes1
 
0.6%
Other values (5)5
 
2.9%

Most occurring characters

ValueCountFrequency (%)
o216
15.6%
n153
11.0%
i131
9.4%
127
9.2%
m96
 
6.9%
e79
 
5.7%
s74
 
5.3%
p71
 
5.1%
t67
 
4.8%
l65
 
4.7%
Other values (16)308
22.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1200
86.5%
Space Separator127
 
9.2%
Uppercase Letter57
 
4.1%
Dash Punctuation3
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o216
18.0%
n153
12.8%
i131
10.9%
m96
8.0%
e79
 
6.6%
s74
 
6.2%
p71
 
5.9%
t67
 
5.6%
l65
 
5.4%
c60
 
5.0%
Other values (11)188
15.7%
Uppercase Letter
ValueCountFrequency (%)
E53
93.0%
P3
 
5.3%
C1
 
1.8%
Space Separator
ValueCountFrequency (%)
127
100.0%
Dash Punctuation
ValueCountFrequency (%)
-3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1257
90.6%
Common130
 
9.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
o216
17.2%
n153
12.2%
i131
10.4%
m96
 
7.6%
e79
 
6.3%
s74
 
5.9%
p71
 
5.6%
t67
 
5.3%
l65
 
5.2%
c60
 
4.8%
Other values (14)245
19.5%
Common
ValueCountFrequency (%)
127
97.7%
-3
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII1343
96.8%
None44
 
3.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o216
16.1%
n153
11.4%
i131
9.8%
127
9.5%
m96
 
7.1%
e79
 
5.9%
s74
 
5.5%
p71
 
5.3%
t67
 
5.0%
l65
 
4.8%
Other values (12)264
19.7%
None
ValueCountFrequency (%)
é33
75.0%
ç4
 
9.1%
ã4
 
9.1%
ó3
 
6.8%

posdoc
Categorical

HIGH CORRELATION

Distinct8
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Memory size584.0 B
Certidão de Nascimento Carteira de Identidade (RG) CPF Carteira de Trabalho Título de Eleitor
43 
Certidão de Nascimento Carteira de Identidade (RG) CPF Título de Eleitor
 
3
Certidão de Nascimento Carteira de Identidade (RG) CPF Carteira de Trabalho
 
3
Certidão de Nascimento Carteira de Identidade (RG) CPF
 
3
Certidão de Nascimento Carteira de Identidade (RG)
 
2
Other values (3)
 
3

Length

Max length93
Median length93
Mean length84.92982456
Min length27

Characters and Unicode

Total characters4841
Distinct characters29
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)5.3%

Sample

1st rowCertidão de Nascimento Carteira de Identidade (RG) CPF Carteira de Trabalho Título de Eleitor
2nd rowCertidão de Nascimento Carteira de Identidade (RG) CPF Carteira de Trabalho Título de Eleitor
3rd rowCertidão de Nascimento Carteira de Identidade (RG)
4th rowCertidão de Nascimento Carteira de Identidade (RG) CPF Título de Eleitor
5th rowCertidão de Nascimento Carteira de Identidade (RG) CPF Carteira de Trabalho

Common Values

ValueCountFrequency (%)
Certidão de Nascimento Carteira de Identidade (RG) CPF Carteira de Trabalho Título de Eleitor43
75.4%
Certidão de Nascimento Carteira de Identidade (RG) CPF Título de Eleitor3
 
5.3%
Certidão de Nascimento Carteira de Identidade (RG) CPF Carteira de Trabalho3
 
5.3%
Certidão de Nascimento Carteira de Identidade (RG) CPF3
 
5.3%
Certidão de Nascimento Carteira de Identidade (RG)2
 
3.5%
Certidão de Nascimento CPF Carteira de Trabalho1
 
1.8%
Carteira de Identidade (RG)1
 
1.8%
Certidão de Nascimento CPF Carteira de Trabalho Título de Eleitor1
 
1.8%

Length

2022-05-31T15:05:22.717872image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:22.860491image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
de206
28.3%
carteira103
14.2%
certidão56
 
7.7%
nascimento56
 
7.7%
identidade55
 
7.6%
rg55
 
7.6%
cpf54
 
7.4%
trabalho48
 
6.6%
título47
 
6.5%
eleitor47
 
6.5%

Most occurring characters

ValueCountFrequency (%)
670
13.8%
e578
11.9%
d427
 
8.8%
a413
 
8.5%
t364
 
7.5%
r357
 
7.4%
i317
 
6.5%
o254
 
5.2%
C213
 
4.4%
l142
 
2.9%
Other values (19)1106
22.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3377
69.8%
Uppercase Letter684
 
14.1%
Space Separator670
 
13.8%
Open Punctuation55
 
1.1%
Close Punctuation55
 
1.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e578
17.1%
d427
12.6%
a413
12.2%
t364
10.8%
r357
10.6%
i317
9.4%
o254
7.5%
l142
 
4.2%
n111
 
3.3%
s56
 
1.7%
Other values (7)358
10.6%
Uppercase Letter
ValueCountFrequency (%)
C213
31.1%
T95
13.9%
N56
 
8.2%
I55
 
8.0%
R55
 
8.0%
G55
 
8.0%
P54
 
7.9%
F54
 
7.9%
E47
 
6.9%
Space Separator
ValueCountFrequency (%)
670
100.0%
Open Punctuation
ValueCountFrequency (%)
(55
100.0%
Close Punctuation
ValueCountFrequency (%)
)55
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4061
83.9%
Common780
 
16.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e578
14.2%
d427
10.5%
a413
10.2%
t364
9.0%
r357
8.8%
i317
 
7.8%
o254
 
6.3%
C213
 
5.2%
l142
 
3.5%
n111
 
2.7%
Other values (16)885
21.8%
Common
ValueCountFrequency (%)
670
85.9%
(55
 
7.1%
)55
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII4738
97.9%
None103
 
2.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
670
14.1%
e578
12.2%
d427
9.0%
a413
8.7%
t364
 
7.7%
r357
 
7.5%
i317
 
6.7%
o254
 
5.4%
C213
 
4.5%
l142
 
3.0%
Other values (17)1003
21.2%
None
ValueCountFrequency (%)
ã56
54.4%
í47
45.6%

possedoc
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)3.6%
Missing1
Missing (%)1.8%
Memory size584.0 B
Sim
48 
Não

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters168
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowSim
3rd rowSim
4th rowNão
5th rowSim

Common Values

ValueCountFrequency (%)
Sim48
84.2%
Não8
 
14.0%
(Missing)1
 
1.8%

Length

2022-05-31T15:05:23.082644image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:23.223237image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim48
85.7%
não8
 
14.3%

Most occurring characters

ValueCountFrequency (%)
S48
28.6%
i48
28.6%
m48
28.6%
N8
 
4.8%
ã8
 
4.8%
o8
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter112
66.7%
Uppercase Letter56
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i48
42.9%
m48
42.9%
ã8
 
7.1%
o8
 
7.1%
Uppercase Letter
ValueCountFrequency (%)
S48
85.7%
N8
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin168
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S48
28.6%
i48
28.6%
m48
28.6%
N8
 
4.8%
ã8
 
4.8%
o8
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII160
95.2%
None8
 
4.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S48
30.0%
i48
30.0%
m48
30.0%
N8
 
5.0%
o8
 
5.0%
None
ValueCountFrequency (%)
ã8
100.0%

tpnaoposse
Categorical

HIGH CORRELATION
MISSING

Distinct6
Distinct (%)75.0%
Missing49
Missing (%)86.0%
Memory size584.0 B
Certidão de Nascimento Carteira de Trabalho Título de Eleitor
Carteira de Trabalho Título de Eleitor
Certidão de Nascimento Carteira de Identidade (RG)
Carteira de Identidade (RG) Carteira de Trabalho
Certidão de Nascimento CPF Carteira de Trabalho Título de Eleitor

Length

Max length65
Median length55.5
Mean length50.5
Min length20

Characters and Unicode

Total characters404
Distinct characters29
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)62.5%

Sample

1st rowCarteira de Trabalho Título de Eleitor
2nd rowCertidão de Nascimento Carteira de Trabalho Título de Eleitor
3rd rowCertidão de Nascimento Carteira de Trabalho Título de Eleitor
4th rowCertidão de Nascimento Carteira de Identidade (RG)
5th rowCertidão de Nascimento Carteira de Trabalho Título de Eleitor

Common Values

ValueCountFrequency (%)
Certidão de Nascimento Carteira de Trabalho Título de Eleitor3
 
5.3%
Carteira de Trabalho Título de Eleitor1
 
1.8%
Certidão de Nascimento Carteira de Identidade (RG)1
 
1.8%
Carteira de Identidade (RG) Carteira de Trabalho1
 
1.8%
Certidão de Nascimento CPF Carteira de Trabalho Título de Eleitor1
 
1.8%
Carteira de Trabalho1
 
1.8%
(Missing)49
86.0%

Length

2022-05-31T15:05:23.340958image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:23.491555image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
de19
31.7%
carteira9
15.0%
trabalho7
 
11.7%
certidão5
 
8.3%
nascimento5
 
8.3%
título5
 
8.3%
eleitor5
 
8.3%
identidade2
 
3.3%
rg2
 
3.3%
cpf1
 
1.7%

Most occurring characters

ValueCountFrequency (%)
52
12.9%
e47
11.6%
a39
9.7%
r35
8.7%
t31
 
7.7%
d30
 
7.4%
o27
 
6.7%
i26
 
6.4%
l17
 
4.2%
C15
 
3.7%
Other values (19)85
21.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter303
75.0%
Space Separator52
 
12.9%
Uppercase Letter45
 
11.1%
Open Punctuation2
 
0.5%
Close Punctuation2
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e47
15.5%
a39
12.9%
r35
11.6%
t31
10.2%
d30
9.9%
o27
8.9%
i26
8.6%
l17
 
5.6%
h7
 
2.3%
b7
 
2.3%
Other values (7)37
12.2%
Uppercase Letter
ValueCountFrequency (%)
C15
33.3%
T12
26.7%
N5
 
11.1%
E5
 
11.1%
I2
 
4.4%
R2
 
4.4%
G2
 
4.4%
P1
 
2.2%
F1
 
2.2%
Space Separator
ValueCountFrequency (%)
52
100.0%
Open Punctuation
ValueCountFrequency (%)
(2
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin348
86.1%
Common56
 
13.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e47
13.5%
a39
11.2%
r35
10.1%
t31
8.9%
d30
8.6%
o27
 
7.8%
i26
 
7.5%
l17
 
4.9%
C15
 
4.3%
T12
 
3.4%
Other values (16)69
19.8%
Common
ValueCountFrequency (%)
52
92.9%
(2
 
3.6%
)2
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII394
97.5%
None10
 
2.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
52
13.2%
e47
11.9%
a39
9.9%
r35
8.9%
t31
7.9%
d30
 
7.6%
o27
 
6.9%
i26
 
6.6%
l17
 
4.3%
C15
 
3.8%
Other values (17)75
19.0%
None
ValueCountFrequency (%)
ã5
50.0%
í5
50.0%

ufnasc
Categorical

HIGH CORRELATION

Distinct9
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Memory size584.0 B
Rio de Janeiro
48 
Rio Grande do Norte
 
2
Sergipe
 
1
Ceará
 
1
São Paulo
 
1
Other values (4)
 
4

Length

Max length19
Median length14
Mean length13.43859649
Min length4

Characters and Unicode

Total characters766
Distinct characters30
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)12.3%

Sample

1st rowRio de Janeiro
2nd rowSergipe
3rd rowRio de Janeiro
4th rowCeará
5th rowRio de Janeiro

Common Values

ValueCountFrequency (%)
Rio de Janeiro48
84.2%
Rio Grande do Norte2
 
3.5%
Sergipe1
 
1.8%
Ceará1
 
1.8%
São Paulo1
 
1.8%
Amazonas1
 
1.8%
Pará1
 
1.8%
Paraíba1
 
1.8%
Distrito Federal1
 
1.8%

Length

2022-05-31T15:05:23.664095image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:23.811661image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
rio50
31.1%
de48
29.8%
janeiro48
29.8%
grande2
 
1.2%
do2
 
1.2%
norte2
 
1.2%
sergipe1
 
0.6%
ceará1
 
0.6%
são1
 
0.6%
paulo1
 
0.6%
Other values (5)5
 
3.1%

Most occurring characters

ValueCountFrequency (%)
o106
13.8%
e105
13.7%
104
13.6%
i101
13.2%
a59
7.7%
r58
7.6%
d53
6.9%
n51
6.7%
R50
6.5%
J48
6.3%
Other values (20)31
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter551
71.9%
Uppercase Letter111
 
14.5%
Space Separator104
 
13.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o106
19.2%
e105
19.1%
i101
18.3%
a59
10.7%
r58
10.5%
d53
9.6%
n51
9.3%
t4
 
0.7%
l2
 
0.4%
s2
 
0.4%
Other values (9)10
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
R50
45.0%
J48
43.2%
P3
 
2.7%
N2
 
1.8%
S2
 
1.8%
G2
 
1.8%
D1
 
0.9%
A1
 
0.9%
C1
 
0.9%
F1
 
0.9%
Space Separator
ValueCountFrequency (%)
104
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin662
86.4%
Common104
 
13.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
o106
16.0%
e105
15.9%
i101
15.3%
a59
8.9%
r58
8.8%
d53
8.0%
n51
7.7%
R50
7.6%
J48
7.3%
t4
 
0.6%
Other values (19)27
 
4.1%
Common
ValueCountFrequency (%)
104
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII762
99.5%
None4
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o106
13.9%
e105
13.8%
104
13.6%
i101
13.3%
a59
7.7%
r58
7.6%
d53
7.0%
n51
6.7%
R50
6.6%
J48
6.3%
Other values (17)27
 
3.5%
None
ValueCountFrequency (%)
á2
50.0%
í1
25.0%
ã1
25.0%

motvimigr
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing57
Missing (%)100.0%
Memory size584.0 B

retifsoc
Categorical

HIGH CORRELATION

Distinct4
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size584.0 B
Não
27 
sem resposta
18 
Sim
10 
Não desejo
 
2

Length

Max length12
Median length3
Mean length6.087719298
Min length3

Characters and Unicode

Total characters347
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão
2nd rowNão
3rd rowNão
4th rowNão
5th rowNão

Common Values

ValueCountFrequency (%)
Não27
47.4%
sem resposta18
31.6%
Sim10
 
17.5%
Não desejo2
 
3.5%

Length

2022-05-31T15:05:23.948295image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:24.077948image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não29
37.7%
sem18
23.4%
resposta18
23.4%
sim10
 
13.0%
desejo2
 
2.6%

Most occurring characters

ValueCountFrequency (%)
s56
16.1%
o49
14.1%
e40
11.5%
N29
8.4%
ã29
8.4%
m28
8.1%
20
 
5.8%
r18
 
5.2%
p18
 
5.2%
t18
 
5.2%
Other values (5)42
12.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter288
83.0%
Uppercase Letter39
 
11.2%
Space Separator20
 
5.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s56
19.4%
o49
17.0%
e40
13.9%
ã29
10.1%
m28
9.7%
r18
 
6.2%
p18
 
6.2%
t18
 
6.2%
a18
 
6.2%
i10
 
3.5%
Other values (2)4
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
N29
74.4%
S10
 
25.6%
Space Separator
ValueCountFrequency (%)
20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin327
94.2%
Common20
 
5.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
s56
17.1%
o49
15.0%
e40
12.2%
N29
8.9%
ã29
8.9%
m28
8.6%
r18
 
5.5%
p18
 
5.5%
t18
 
5.5%
a18
 
5.5%
Other values (4)24
7.3%
Common
ValueCountFrequency (%)
20
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII318
91.6%
None29
 
8.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s56
17.6%
o49
15.4%
e40
12.6%
N29
9.1%
m28
8.8%
20
 
6.3%
r18
 
5.7%
p18
 
5.7%
t18
 
5.7%
a18
 
5.7%
Other values (4)24
7.5%
None
ValueCountFrequency (%)
ã29
100.0%

retifgrat
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)20.0%
Missing47
Missing (%)82.5%
Memory size584.0 B
Sim
Não

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters30
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)10.0%

Sample

1st rowSim
2nd rowSim
3rd rowSim
4th rowSim
5th rowSim

Common Values

ValueCountFrequency (%)
Sim9
 
15.8%
Não1
 
1.8%
(Missing)47
82.5%

Length

2022-05-31T15:05:24.190645image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:24.293370image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim9
90.0%
não1
 
10.0%

Most occurring characters

ValueCountFrequency (%)
S9
30.0%
i9
30.0%
m9
30.0%
N1
 
3.3%
ã1
 
3.3%
o1
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter20
66.7%
Uppercase Letter10
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i9
45.0%
m9
45.0%
ã1
 
5.0%
o1
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
S9
90.0%
N1
 
10.0%

Most occurring scripts

ValueCountFrequency (%)
Latin30
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S9
30.0%
i9
30.0%
m9
30.0%
N1
 
3.3%
ã1
 
3.3%
o1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII29
96.7%
None1
 
3.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S9
31.0%
i9
31.0%
m9
31.0%
N1
 
3.4%
o1
 
3.4%
None
ValueCountFrequency (%)
ã1
100.0%

relacamor
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size584.0 B
Não
38 
Sim
19 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters171
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowNão
3rd rowNão
4th rowNão
5th rowNão

Common Values

ValueCountFrequency (%)
Não38
66.7%
Sim19
33.3%

Length

2022-05-31T15:05:24.384127image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:24.495875image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não38
66.7%
sim19
33.3%

Most occurring characters

ValueCountFrequency (%)
N38
22.2%
ã38
22.2%
o38
22.2%
S19
11.1%
i19
11.1%
m19
11.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter114
66.7%
Uppercase Letter57
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
ã38
33.3%
o38
33.3%
i19
16.7%
m19
16.7%
Uppercase Letter
ValueCountFrequency (%)
N38
66.7%
S19
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin171
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N38
22.2%
ã38
22.2%
o38
22.2%
S19
11.1%
i19
11.1%
m19
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII133
77.8%
None38
 
22.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N38
28.6%
o38
28.6%
S19
14.3%
i19
14.3%
m19
14.3%
None
ValueCountFrequency (%)
ã38
100.0%

qtdmora
Categorical

HIGH CORRELATION
MISSING

Distinct7
Distinct (%)13.0%
Missing3
Missing (%)5.3%
Memory size584.0 B
Moro sozinha
21 
Moro com duas pessoas
Moro com três pessoas
Moro com mais que cinco pessoas
Moro com quatro pessoas
Other values (2)

Length

Max length31
Median length23
Mean length18.7037037
Min length12

Characters and Unicode

Total characters1010
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st rowMoro com mais que cinco pessoas
2nd rowMoro com uma pessoa
3rd rowMoro com quatro pessoas
4th rowMoro com quatro pessoas
5th rowMoro com quatro pessoas

Common Values

ValueCountFrequency (%)
Moro sozinha21
36.8%
Moro com duas pessoas9
15.8%
Moro com três pessoas7
 
12.3%
Moro com mais que cinco pessoas6
 
10.5%
Moro com quatro pessoas6
 
10.5%
Moro com uma pessoa4
 
7.0%
Moro com cinco pessoas1
 
1.8%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:24.608568image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:24.754139image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
moro54
29.0%
com33
17.7%
pessoas29
15.6%
sozinha21
 
11.3%
duas9
 
4.8%
três7
 
3.8%
cinco7
 
3.8%
mais6
 
3.2%
que6
 
3.2%
quatro6
 
3.2%
Other values (2)8
 
4.3%

Most occurring characters

ValueCountFrequency (%)
o208
20.6%
s138
13.7%
132
13.1%
a79
 
7.8%
r67
 
6.6%
M54
 
5.3%
c47
 
4.7%
m43
 
4.3%
e39
 
3.9%
i34
 
3.4%
Other values (9)169
16.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter824
81.6%
Space Separator132
 
13.1%
Uppercase Letter54
 
5.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o208
25.2%
s138
16.7%
a79
 
9.6%
r67
 
8.1%
c47
 
5.7%
m43
 
5.2%
e39
 
4.7%
i34
 
4.1%
p33
 
4.0%
n28
 
3.4%
Other values (7)108
13.1%
Space Separator
ValueCountFrequency (%)
132
100.0%
Uppercase Letter
ValueCountFrequency (%)
M54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin878
86.9%
Common132
 
13.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o208
23.7%
s138
15.7%
a79
 
9.0%
r67
 
7.6%
M54
 
6.2%
c47
 
5.4%
m43
 
4.9%
e39
 
4.4%
i34
 
3.9%
p33
 
3.8%
Other values (8)136
15.5%
Common
ValueCountFrequency (%)
132
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1003
99.3%
None7
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o208
20.7%
s138
13.8%
132
13.2%
a79
 
7.9%
r67
 
6.7%
M54
 
5.4%
c47
 
4.7%
m43
 
4.3%
e39
 
3.9%
i34
 
3.4%
Other values (8)162
16.2%
None
ValueCountFrequency (%)
ê7
100.0%

grpmora
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)9.1%
Missing24
Missing (%)42.1%
Memory size584.0 B
Família
31 
Amigos
 
1
Não consigo especificar um grupo apenas
 
1

Length

Max length39
Median length7
Mean length7.939393939
Min length6

Characters and Unicode

Total characters262
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)6.1%

Sample

1st rowFamília
2nd rowAmigos
3rd rowFamília
4th rowFamília
5th rowFamília

Common Values

ValueCountFrequency (%)
Família31
54.4%
Amigos1
 
1.8%
Não consigo especificar um grupo apenas1
 
1.8%
(Missing)24
42.1%

Length

2022-05-31T15:05:24.904735image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:25.023417image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
família31
81.6%
amigos1
 
2.6%
não1
 
2.6%
consigo1
 
2.6%
especificar1
 
2.6%
um1
 
2.6%
grupo1
 
2.6%
apenas1
 
2.6%

Most occurring characters

ValueCountFrequency (%)
a65
24.8%
i35
13.4%
m33
12.6%
F31
11.8%
í31
11.8%
l31
11.8%
o5
 
1.9%
5
 
1.9%
s4
 
1.5%
e3
 
1.1%
Other values (10)19
 
7.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter224
85.5%
Uppercase Letter33
 
12.6%
Space Separator5
 
1.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a65
29.0%
i35
15.6%
m33
14.7%
í31
13.8%
l31
13.8%
o5
 
2.2%
s4
 
1.8%
e3
 
1.3%
g3
 
1.3%
p3
 
1.3%
Other values (6)11
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
F31
93.9%
A1
 
3.0%
N1
 
3.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin257
98.1%
Common5
 
1.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a65
25.3%
i35
13.6%
m33
12.8%
F31
12.1%
í31
12.1%
l31
12.1%
o5
 
1.9%
s4
 
1.6%
e3
 
1.2%
g3
 
1.2%
Other values (9)16
 
6.2%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII230
87.8%
None32
 
12.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a65
28.3%
i35
15.2%
m33
14.3%
F31
13.5%
l31
13.5%
o5
 
2.2%
5
 
2.2%
s4
 
1.7%
e3
 
1.3%
g3
 
1.3%
Other values (8)15
 
6.5%
None
ValueCountFrequency (%)
í31
96.9%
ã1
 
3.1%

famidgen
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)7.4%
Missing3
Missing (%)5.3%
Memory size584.0 B
Eu mesma contei
34 
De outras maneiras
13 
Souberam por terceiros
Não sabem
 
1

Length

Max length22
Median length15
Mean length16.38888889
Min length9

Characters and Unicode

Total characters885
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st rowEu mesma contei
2nd rowEu mesma contei
3rd rowDe outras maneiras
4th rowEu mesma contei
5th rowEu mesma contei

Common Values

ValueCountFrequency (%)
Eu mesma contei34
59.6%
De outras maneiras13
 
22.8%
Souberam por terceiros6
 
10.5%
Não sabem1
 
1.8%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:25.138154image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:25.262779image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
eu34
21.1%
mesma34
21.1%
contei34
21.1%
de13
 
8.1%
outras13
 
8.1%
maneiras13
 
8.1%
souberam6
 
3.7%
por6
 
3.7%
terceiros6
 
3.7%
não1
 
0.6%

Most occurring characters

ValueCountFrequency (%)
e113
12.8%
107
12.1%
m88
9.9%
a80
9.0%
s67
7.6%
o66
7.5%
u53
 
6.0%
t53
 
6.0%
i53
 
6.0%
r50
 
5.6%
Other values (9)155
17.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter724
81.8%
Space Separator107
 
12.1%
Uppercase Letter54
 
6.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e113
15.6%
m88
12.2%
a80
11.0%
s67
9.3%
o66
9.1%
u53
7.3%
t53
7.3%
i53
7.3%
r50
6.9%
n47
6.5%
Other values (4)54
7.5%
Uppercase Letter
ValueCountFrequency (%)
E34
63.0%
D13
 
24.1%
S6
 
11.1%
N1
 
1.9%
Space Separator
ValueCountFrequency (%)
107
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin778
87.9%
Common107
 
12.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e113
14.5%
m88
11.3%
a80
10.3%
s67
8.6%
o66
8.5%
u53
6.8%
t53
6.8%
i53
6.8%
r50
6.4%
n47
6.0%
Other values (8)108
13.9%
Common
ValueCountFrequency (%)
107
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII884
99.9%
None1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e113
12.8%
107
12.1%
m88
10.0%
a80
9.0%
s67
7.6%
o66
7.5%
u53
 
6.0%
t53
 
6.0%
i53
 
6.0%
r50
 
5.7%
Other values (8)154
17.4%
None
ValueCountFrequency (%)
ã1
100.0%

ididgen
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct17
Distinct (%)32.7%
Missing5
Missing (%)8.8%
Infinite0
Infinite (%)0.0%
Mean15.53846154
Minimum8
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size584.0 B
2022-05-31T15:05:25.373481image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile9.55
Q113
median15
Q318
95-th percentile21.9
Maximum31
Range23
Interquartile range (IQR)5

Descriptive statistics

Standard deviation4.202993977
Coefficient of variation (CV)0.2704897114
Kurtosis2.672524038
Mean15.53846154
Median Absolute Deviation (MAD)2
Skewness1.001540149
Sum808
Variance17.66515837
MonotonicityNot monotonic
2022-05-31T15:05:25.477246image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
159
15.8%
166
10.5%
186
10.5%
136
10.5%
174
7.0%
104
7.0%
143
 
5.3%
122
 
3.5%
212
 
3.5%
202
 
3.5%
Other values (7)8
14.0%
(Missing)5
8.8%
ValueCountFrequency (%)
81
 
1.8%
92
 
3.5%
104
7.0%
111
 
1.8%
122
 
3.5%
136
10.5%
143
 
5.3%
159
15.8%
166
10.5%
174
7.0%
ValueCountFrequency (%)
311
 
1.8%
251
 
1.8%
231
 
1.8%
212
 
3.5%
202
 
3.5%
191
 
1.8%
186
10.5%
174
7.0%
166
10.5%
159
15.8%

famreac
Categorical

HIGH CORRELATION
MISSING

Distinct30
Distinct (%)56.6%
Missing4
Missing (%)7.0%
Memory size584.0 B
Me apoiaram/acolheram
10 
Me expulsaram de casa
Me apoiaram/acolheram Ficaram preocupados com a violência
Meus pais não me acolheram mas outras pessoas da família sim
Me levaram para igreja/rezaram Ficaram preocupados com a violência Minha mãe me acolheu e meu pai não
 
2
Other values (25)
29 

Length

Max length129
Median length115
Mean length54.50943396
Min length11

Characters and Unicode

Total characters2889
Distinct characters31
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)39.6%

Sample

1st rowMe apoiaram/acolheram
2nd rowMeus pais não me acolheram mas outras pessoas da família sim
3rd rowMe apoiaram/acolheram Minha mãe me acolheu e meu pai não
4th rowMe apoiaram/acolheram
5th rowMe apoiaram/acolheram

Common Values

ValueCountFrequency (%)
Me apoiaram/acolheram10
17.5%
Me expulsaram de casa5
 
8.8%
Me apoiaram/acolheram Ficaram preocupados com a violência4
 
7.0%
Meus pais não me acolheram mas outras pessoas da família sim3
 
5.3%
Me levaram para igreja/rezaram Ficaram preocupados com a violência Minha mãe me acolheu e meu pai não2
 
3.5%
Me apoiaram/acolheram Não falaram nada2
 
3.5%
Não falaram nada2
 
3.5%
Minha mãe me acolheu e meu pai não2
 
3.5%
Me xingaram Me levaram para igreja/rezaram2
 
3.5%
Me agrediram Me xingaram Disseram que era apenas uma fase Meus pais não me acolheram mas outras pessoas da família sim1
 
1.8%
Other values (20)20
35.1%
(Missing)4
 
7.0%

Length

2022-05-31T15:05:25.610416image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
me67
 
13.9%
não30
 
6.2%
apoiaram/acolheram19
 
4.0%
preocupados16
 
3.3%
violência16
 
3.3%
com16
 
3.3%
a16
 
3.3%
ficaram16
 
3.3%
meu13
 
2.7%
e13
 
2.7%
Other values (29)259
53.8%

Most occurring characters

ValueCountFrequency (%)
a482
16.7%
428
14.8%
e260
 
9.0%
m214
 
7.4%
o175
 
6.1%
r162
 
5.6%
i150
 
5.2%
s146
 
5.1%
c113
 
3.9%
p105
 
3.6%
Other values (21)654
22.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2338
80.9%
Space Separator428
 
14.8%
Uppercase Letter99
 
3.4%
Other Punctuation24
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a482
20.6%
e260
11.1%
m214
9.2%
o175
 
7.5%
r162
 
6.9%
i150
 
6.4%
s146
 
6.2%
c113
 
4.8%
p105
 
4.5%
u87
 
3.7%
Other values (15)444
19.0%
Uppercase Letter
ValueCountFrequency (%)
M67
67.7%
F16
 
16.2%
D9
 
9.1%
N7
 
7.1%
Space Separator
ValueCountFrequency (%)
428
100.0%
Other Punctuation
ValueCountFrequency (%)
/24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2437
84.4%
Common452
 
15.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a482
19.8%
e260
10.7%
m214
 
8.8%
o175
 
7.2%
r162
 
6.6%
i150
 
6.2%
s146
 
6.0%
c113
 
4.6%
p105
 
4.3%
u87
 
3.6%
Other values (19)543
22.3%
Common
ValueCountFrequency (%)
428
94.7%
/24
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII2820
97.6%
None69
 
2.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a482
17.1%
428
15.2%
e260
9.2%
m214
 
7.6%
o175
 
6.2%
r162
 
5.7%
i150
 
5.3%
s146
 
5.2%
c113
 
4.0%
p105
 
3.7%
Other values (18)585
20.7%
None
ValueCountFrequency (%)
ã43
62.3%
ê16
 
23.2%
í10
 
14.5%

relafam
Categorical

HIGH CORRELATION
MISSING

Distinct5
Distinct (%)9.3%
Missing3
Missing (%)5.3%
Memory size584.0 B
Boa
23 
Excelente
14 
Indiferente
Ruim
Péssimo

Length

Max length11
Median length9
Mean length6.259259259
Min length3

Characters and Unicode

Total characters338
Distinct characters21
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBoa
2nd rowBoa
3rd rowBoa
4th rowBoa
5th rowBoa

Common Values

ValueCountFrequency (%)
Boa23
40.4%
Excelente14
24.6%
Indiferente9
 
15.8%
Ruim4
 
7.0%
Péssimo4
 
7.0%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:25.750849image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:25.879502image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
boa23
42.6%
excelente14
25.9%
indiferente9
 
16.7%
ruim4
 
7.4%
péssimo4
 
7.4%

Most occurring characters

ValueCountFrequency (%)
e69
20.4%
n32
 
9.5%
o27
 
8.0%
B23
 
6.8%
a23
 
6.8%
t23
 
6.8%
i17
 
5.0%
E14
 
4.1%
x14
 
4.1%
c14
 
4.1%
Other values (11)82
24.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter284
84.0%
Uppercase Letter54
 
16.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e69
24.3%
n32
11.3%
o27
 
9.5%
a23
 
8.1%
t23
 
8.1%
i17
 
6.0%
x14
 
4.9%
c14
 
4.9%
l14
 
4.9%
f9
 
3.2%
Other values (6)42
14.8%
Uppercase Letter
ValueCountFrequency (%)
B23
42.6%
E14
25.9%
I9
 
16.7%
R4
 
7.4%
P4
 
7.4%

Most occurring scripts

ValueCountFrequency (%)
Latin338
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e69
20.4%
n32
 
9.5%
o27
 
8.0%
B23
 
6.8%
a23
 
6.8%
t23
 
6.8%
i17
 
5.0%
E14
 
4.1%
x14
 
4.1%
c14
 
4.1%
Other values (11)82
24.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII334
98.8%
None4
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e69
20.7%
n32
9.6%
o27
 
8.1%
B23
 
6.9%
a23
 
6.9%
t23
 
6.9%
i17
 
5.1%
E14
 
4.2%
x14
 
4.2%
c14
 
4.2%
Other values (10)78
23.4%
None
ValueCountFrequency (%)
é4
100.0%

respons
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)7.4%
Missing3
Missing (%)5.3%
Memory size584.0 B
Não, não sou responsável por ninguém em meu ambiente domiciliar
39 
Sim, depende de meus cuidados, porém não financeiros
Sim depende financeiramente e de cuidados
Sim, depende de mim financeiramente

Length

Max length63
Median length63
Mean length57.66666667
Min length35

Characters and Unicode

Total characters3114
Distinct characters25
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim depende financeiramente e de cuidados
2nd rowNão, não sou responsável por ninguém em meu ambiente domiciliar
3rd rowNão, não sou responsável por ninguém em meu ambiente domiciliar
4th rowNão, não sou responsável por ninguém em meu ambiente domiciliar
5th rowNão, não sou responsável por ninguém em meu ambiente domiciliar

Common Values

ValueCountFrequency (%)
Não, não sou responsável por ninguém em meu ambiente domiciliar39
68.4%
Sim, depende de meus cuidados, porém não financeiros6
 
10.5%
Sim depende financeiramente e de cuidados5
 
8.8%
Sim, depende de mim financeiramente4
 
7.0%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:26.003174image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:26.136816image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não84
17.2%
responsável39
8.0%
por39
8.0%
ninguém39
8.0%
em39
8.0%
meu39
8.0%
ambiente39
8.0%
domiciliar39
8.0%
sou39
8.0%
de15
 
3.1%
Other values (9)77
15.8%

Most occurring characters

ValueCountFrequency (%)
434
13.9%
e338
10.9%
o263
 
8.4%
i255
 
8.2%
n255
 
8.2%
m239
 
7.7%
s140
 
4.5%
r138
 
4.4%
u134
 
4.3%
a113
 
3.6%
Other values (15)805
25.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2571
82.6%
Space Separator434
 
13.9%
Other Punctuation55
 
1.8%
Uppercase Letter54
 
1.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e338
13.1%
o263
10.2%
i255
9.9%
n255
9.9%
m239
9.3%
s140
 
5.4%
r138
 
5.4%
u134
 
5.2%
a113
 
4.4%
d106
 
4.1%
Other values (11)590
22.9%
Uppercase Letter
ValueCountFrequency (%)
N39
72.2%
S15
 
27.8%
Space Separator
ValueCountFrequency (%)
434
100.0%
Other Punctuation
ValueCountFrequency (%)
,55
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2625
84.3%
Common489
 
15.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e338
12.9%
o263
10.0%
i255
 
9.7%
n255
 
9.7%
m239
 
9.1%
s140
 
5.3%
r138
 
5.3%
u134
 
5.1%
a113
 
4.3%
d106
 
4.0%
Other values (13)644
24.5%
Common
ValueCountFrequency (%)
434
88.8%
,55
 
11.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII2946
94.6%
None168
 
5.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
434
14.7%
e338
11.5%
o263
8.9%
i255
8.7%
n255
8.7%
m239
 
8.1%
s140
 
4.8%
r138
 
4.7%
u134
 
4.5%
a113
 
3.8%
Other values (12)637
21.6%
None
ValueCountFrequency (%)
ã84
50.0%
é45
26.8%
á39
23.2%

violdom
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)5.6%
Missing3
Missing (%)5.3%
Memory size584.0 B
Sim
27 
Não
23 
Não sei especificar

Length

Max length19
Median length3
Mean length4.185185185
Min length3

Characters and Unicode

Total characters226
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão
2nd rowSim
3rd rowNão sei especificar
4th rowNão
5th rowNão

Common Values

ValueCountFrequency (%)
Sim27
47.4%
Não23
40.4%
Não sei especificar4
 
7.0%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:26.284420image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:26.403104image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim27
43.5%
não27
43.5%
sei4
 
6.5%
especificar4
 
6.5%

Most occurring characters

ValueCountFrequency (%)
i39
17.3%
S27
11.9%
m27
11.9%
N27
11.9%
ã27
11.9%
o27
11.9%
e12
 
5.3%
8
 
3.5%
s8
 
3.5%
c8
 
3.5%
Other values (4)16
7.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter164
72.6%
Uppercase Letter54
 
23.9%
Space Separator8
 
3.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i39
23.8%
m27
16.5%
ã27
16.5%
o27
16.5%
e12
 
7.3%
s8
 
4.9%
c8
 
4.9%
p4
 
2.4%
f4
 
2.4%
a4
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
S27
50.0%
N27
50.0%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin218
96.5%
Common8
 
3.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
i39
17.9%
S27
12.4%
m27
12.4%
N27
12.4%
ã27
12.4%
o27
12.4%
e12
 
5.5%
s8
 
3.7%
c8
 
3.7%
p4
 
1.8%
Other values (3)12
 
5.5%
Common
ValueCountFrequency (%)
8
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII199
88.1%
None27
 
11.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i39
19.6%
S27
13.6%
m27
13.6%
N27
13.6%
o27
13.6%
e12
 
6.0%
8
 
4.0%
s8
 
4.0%
c8
 
4.0%
p4
 
2.0%
Other values (3)12
 
6.0%
None
ValueCountFrequency (%)
ã27
100.0%

alclfam
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)5.6%
Missing3
Missing (%)5.3%
Memory size584.0 B
Sim
32 
Não
20 
Não sei
 
2

Length

Max length7
Median length3
Mean length3.148148148
Min length3

Characters and Unicode

Total characters170
Distinct characters9
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão
2nd rowNão sei
3rd rowNão
4th rowNão
5th rowSim

Common Values

ValueCountFrequency (%)
Sim32
56.1%
Não20
35.1%
Não sei2
 
3.5%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:26.522823image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:26.644458image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim32
57.1%
não22
39.3%
sei2
 
3.6%

Most occurring characters

ValueCountFrequency (%)
i34
20.0%
S32
18.8%
m32
18.8%
N22
12.9%
ã22
12.9%
o22
12.9%
2
 
1.2%
s2
 
1.2%
e2
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter114
67.1%
Uppercase Letter54
31.8%
Space Separator2
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i34
29.8%
m32
28.1%
ã22
19.3%
o22
19.3%
s2
 
1.8%
e2
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
S32
59.3%
N22
40.7%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin168
98.8%
Common2
 
1.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
i34
20.2%
S32
19.0%
m32
19.0%
N22
13.1%
ã22
13.1%
o22
13.1%
s2
 
1.2%
e2
 
1.2%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII148
87.1%
None22
 
12.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i34
23.0%
S32
21.6%
m32
21.6%
N22
14.9%
o22
14.9%
2
 
1.4%
s2
 
1.4%
e2
 
1.4%
None
ValueCountFrequency (%)
ã22
100.0%

filho
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)7.5%
Missing4
Missing (%)7.0%
Memory size584.0 B
Não e, não pretendo ter
24 
Não, mas quero ter
23 
Sim, filha(s) adotadas
Sim, filha(s) biológicas

Length

Max length24
Median length23
Mean length20.83018868
Min length18

Characters and Unicode

Total characters1104
Distinct characters27
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão e, não pretendo ter
2nd rowNão, mas quero ter
3rd rowNão, mas quero ter
4th rowNão e, não pretendo ter
5th rowNão, mas quero ter

Common Values

ValueCountFrequency (%)
Não e, não pretendo ter24
42.1%
Não, mas quero ter23
40.4%
Sim, filha(s) adotadas3
 
5.3%
Sim, filha(s) biológicas3
 
5.3%
(Missing)4
 
7.0%

Length

2022-05-31T15:05:26.757154image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:26.881013image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não71
30.9%
ter47
20.4%
e24
 
10.4%
pretendo24
 
10.4%
mas23
 
10.0%
quero23
 
10.0%
sim6
 
2.6%
filha(s6
 
2.6%
adotadas3
 
1.3%
biológicas3
 
1.3%

Most occurring characters

ValueCountFrequency (%)
177
16.0%
e142
12.9%
o124
11.2%
r94
8.5%
t74
 
6.7%
ã71
 
6.4%
,53
 
4.8%
n48
 
4.3%
N47
 
4.3%
a41
 
3.7%
Other values (17)233
21.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter809
73.3%
Space Separator177
 
16.0%
Other Punctuation53
 
4.8%
Uppercase Letter53
 
4.8%
Open Punctuation6
 
0.5%
Close Punctuation6
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e142
17.6%
o124
15.3%
r94
11.6%
t74
9.1%
ã71
8.8%
n48
 
5.9%
a41
 
5.1%
s35
 
4.3%
d30
 
3.7%
m29
 
3.6%
Other values (11)121
15.0%
Uppercase Letter
ValueCountFrequency (%)
N47
88.7%
S6
 
11.3%
Space Separator
ValueCountFrequency (%)
177
100.0%
Other Punctuation
ValueCountFrequency (%)
,53
100.0%
Open Punctuation
ValueCountFrequency (%)
(6
100.0%
Close Punctuation
ValueCountFrequency (%)
)6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin862
78.1%
Common242
 
21.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e142
16.5%
o124
14.4%
r94
10.9%
t74
8.6%
ã71
8.2%
n48
 
5.6%
N47
 
5.5%
a41
 
4.8%
s35
 
4.1%
d30
 
3.5%
Other values (13)156
18.1%
Common
ValueCountFrequency (%)
177
73.1%
,53
 
21.9%
(6
 
2.5%
)6
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII1030
93.3%
None74
 
6.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
177
17.2%
e142
13.8%
o124
12.0%
r94
9.1%
t74
 
7.2%
,53
 
5.1%
n48
 
4.7%
N47
 
4.6%
a41
 
4.0%
s35
 
3.4%
Other values (15)195
18.9%
None
ValueCountFrequency (%)
ã71
95.9%
ó3
 
4.1%

contrcs
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)5.6%
Missing3
Missing (%)5.3%
Memory size584.0 B
Casa toda de tijolo e cimento (alvenaria)
51 
Nenhuma das opções acima
 
2
Casa feita na maioria por lona/plástico
 
1

Length

Max length41
Median length41
Mean length40.33333333
Min length24

Characters and Unicode

Total characters2178
Distinct characters27
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st rowNenhuma das opções acima
2nd rowCasa toda de tijolo e cimento (alvenaria)
3rd rowCasa toda de tijolo e cimento (alvenaria)
4th rowCasa toda de tijolo e cimento (alvenaria)
5th rowCasa toda de tijolo e cimento (alvenaria)

Common Values

ValueCountFrequency (%)
Casa toda de tijolo e cimento (alvenaria)51
89.5%
Nenhuma das opções acima2
 
3.5%
Casa feita na maioria por lona/plástico1
 
1.8%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:27.004682image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:27.121370image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
casa52
14.0%
toda51
13.7%
de51
13.7%
tijolo51
13.7%
e51
13.7%
cimento51
13.7%
alvenaria51
13.7%
nenhuma2
 
0.5%
das2
 
0.5%
opções2
 
0.5%
Other values (6)7
 
1.9%

Most occurring characters

ValueCountFrequency (%)
a321
14.7%
317
14.6%
o210
9.6%
e209
9.6%
i159
 
7.3%
t155
 
7.1%
n106
 
4.9%
d104
 
4.8%
l104
 
4.8%
s57
 
2.6%
Other values (17)436
20.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1704
78.2%
Space Separator317
 
14.6%
Uppercase Letter54
 
2.5%
Open Punctuation51
 
2.3%
Close Punctuation51
 
2.3%
Other Punctuation1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a321
18.8%
o210
12.3%
e209
12.3%
i159
9.3%
t155
9.1%
n106
 
6.2%
d104
 
6.1%
l104
 
6.1%
s57
 
3.3%
m56
 
3.3%
Other values (11)223
13.1%
Uppercase Letter
ValueCountFrequency (%)
C52
96.3%
N2
 
3.7%
Space Separator
ValueCountFrequency (%)
317
100.0%
Open Punctuation
ValueCountFrequency (%)
(51
100.0%
Close Punctuation
ValueCountFrequency (%)
)51
100.0%
Other Punctuation
ValueCountFrequency (%)
/1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1758
80.7%
Common420
 
19.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a321
18.3%
o210
11.9%
e209
11.9%
i159
9.0%
t155
8.8%
n106
 
6.0%
d104
 
5.9%
l104
 
5.9%
s57
 
3.2%
m56
 
3.2%
Other values (13)277
15.8%
Common
ValueCountFrequency (%)
317
75.5%
(51
 
12.1%
)51
 
12.1%
/1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII2173
99.8%
None5
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a321
14.8%
317
14.6%
o210
9.7%
e209
9.6%
i159
 
7.3%
t155
 
7.1%
n106
 
4.9%
d104
 
4.8%
l104
 
4.8%
s57
 
2.6%
Other values (14)431
19.8%
None
ValueCountFrequency (%)
ç2
40.0%
õ2
40.0%
á1
20.0%

equiprua
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing57
Missing (%)100.0%
Memory size584.0 B

saneam
Categorical

HIGH CORRELATION
MISSING

Distinct14
Distinct (%)25.9%
Missing3
Missing (%)5.3%
Memory size584.0 B
Água encanada ligada ao sistema de fornecimento público de água Banheiro com ligação à rede de esgoto Caixa d’agua ou cisterna Energia elétrica da rede de abastecimento (irregular)
18 
Água encanada ligada ao sistema de fornecimento público de água Banheiro com ligação à rede de esgoto Caixa d’agua ou cisterna Energia elétrica da rede de abastecimento (regularizada)
14 
Não se aplica
Água encanada ligada ao sistema de fornecimento público de água Banheiro com ligação à rede de esgoto Energia elétrica da rede de abastecimento (regularizada)
Água encanada ligada ao sistema de fornecimento público de água Banheiro com ligação à rede de esgoto Caixa d’agua ou cisterna Energia elétrica da rede de abastecimento (regularizada) Energia elétrica da rede de abastecimento (irregular)
Other values (9)
13 

Length

Max length237
Median length221
Mean length159.9444444
Min length13

Characters and Unicode

Total characters8637
Distinct characters35
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)11.1%

Sample

1st rowNão se aplica
2nd rowBanheiro com ligação à rede de esgoto Caixa d’agua ou cisterna Energia elétrica da rede de abastecimento (regularizada)
3rd rowÁgua encanada ligada ao sistema de fornecimento público de água Energia elétrica da rede de abastecimento (irregular)
4th rowÁgua encanada ligada ao sistema de fornecimento público de água
5th rowEnergia elétrica da rede de abastecimento (irregular)

Common Values

ValueCountFrequency (%)
Água encanada ligada ao sistema de fornecimento público de água Banheiro com ligação à rede de esgoto Caixa d’agua ou cisterna Energia elétrica da rede de abastecimento (irregular)18
31.6%
Água encanada ligada ao sistema de fornecimento público de água Banheiro com ligação à rede de esgoto Caixa d’agua ou cisterna Energia elétrica da rede de abastecimento (regularizada)14
24.6%
Não se aplica3
 
5.3%
Água encanada ligada ao sistema de fornecimento público de água Banheiro com ligação à rede de esgoto Energia elétrica da rede de abastecimento (regularizada)3
 
5.3%
Água encanada ligada ao sistema de fornecimento público de água Banheiro com ligação à rede de esgoto Caixa d’agua ou cisterna Energia elétrica da rede de abastecimento (regularizada) Energia elétrica da rede de abastecimento (irregular)3
 
5.3%
Água encanada ligada ao sistema de fornecimento público de água Banheiro com ligação à rede de esgoto Energia elétrica da rede de abastecimento (irregular)3
 
5.3%
Água encanada ligada ao sistema de fornecimento público de água2
 
3.5%
Energia elétrica da rede de abastecimento (regularizada)2
 
3.5%
Banheiro com ligação à rede de esgoto Caixa d’agua ou cisterna Energia elétrica da rede de abastecimento (regularizada)1
 
1.8%
Água encanada ligada ao sistema de fornecimento público de água Energia elétrica da rede de abastecimento (irregular)1
 
1.8%
Other values (4)4
 
7.0%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:27.238991image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
de193
 
14.5%
rede99
 
7.5%
água94
 
7.1%
energia52
 
3.9%
da52
 
3.9%
abastecimento52
 
3.9%
elétrica52
 
3.9%
público47
 
3.5%
banheiro47
 
3.5%
fornecimento47
 
3.5%
Other values (18)593
44.7%

Most occurring characters

ValueCountFrequency (%)
1274
14.8%
a1078
12.5%
e978
11.3%
i571
 
6.6%
o514
 
6.0%
d501
 
5.8%
r468
 
5.4%
n378
 
4.4%
g378
 
4.4%
t336
 
3.9%
Other values (25)2161
25.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7032
81.4%
Space Separator1274
 
14.8%
Uppercase Letter188
 
2.2%
Close Punctuation52
 
0.6%
Open Punctuation52
 
0.6%
Final Punctuation39
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a1078
15.3%
e978
13.9%
i571
 
8.1%
o514
 
7.3%
d501
 
7.1%
r468
 
6.7%
n378
 
5.4%
g378
 
5.4%
t336
 
4.8%
c331
 
4.7%
Other values (16)1499
21.3%
Uppercase Letter
ValueCountFrequency (%)
E52
27.7%
Á47
25.0%
B47
25.0%
C39
20.7%
N3
 
1.6%
Space Separator
ValueCountFrequency (%)
1274
100.0%
Close Punctuation
ValueCountFrequency (%)
)52
100.0%
Open Punctuation
ValueCountFrequency (%)
(52
100.0%
Final Punctuation
ValueCountFrequency (%)
39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin7220
83.6%
Common1417
 
16.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a1078
14.9%
e978
13.5%
i571
 
7.9%
o514
 
7.1%
d501
 
6.9%
r468
 
6.5%
n378
 
5.2%
g378
 
5.2%
t336
 
4.7%
c331
 
4.6%
Other values (21)1687
23.4%
Common
ValueCountFrequency (%)
1274
89.9%
)52
 
3.7%
(52
 
3.7%
39
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII8261
95.6%
None337
 
3.9%
Punctuation39
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1274
15.4%
a1078
13.0%
e978
11.8%
i571
 
6.9%
o514
 
6.2%
d501
 
6.1%
r468
 
5.7%
n378
 
4.6%
g378
 
4.6%
t336
 
4.1%
Other values (17)1785
21.6%
None
ValueCountFrequency (%)
é52
15.4%
ã50
14.8%
à47
13.9%
Á47
13.9%
ç47
13.9%
á47
13.9%
ú47
13.9%
Punctuation
ValueCountFrequency (%)
39
100.0%

proprcs
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)7.4%
Missing3
Missing (%)5.3%
Memory size584.0 B
Casa própria
31 
Paga aluguel
14 
Mora de favor
Casa própria financiada
 
2

Length

Max length23
Median length12
Mean length12.53703704
Min length12

Characters and Unicode

Total characters677
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMora de favor
2nd rowPaga aluguel
3rd rowCasa própria
4th rowCasa própria
5th rowCasa própria

Common Values

ValueCountFrequency (%)
Casa própria31
54.4%
Paga aluguel14
24.6%
Mora de favor7
 
12.3%
Casa própria financiada2
 
3.5%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:27.373673image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:27.496303image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
casa33
28.2%
própria33
28.2%
paga14
12.0%
aluguel14
12.0%
mora7
 
6.0%
de7
 
6.0%
favor7
 
6.0%
financiada2
 
1.7%

Most occurring characters

ValueCountFrequency (%)
a161
23.8%
r80
11.8%
p66
9.7%
63
 
9.3%
i37
 
5.5%
C33
 
4.9%
s33
 
4.9%
ó33
 
4.9%
u28
 
4.1%
l28
 
4.1%
Other values (10)115
17.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter560
82.7%
Space Separator63
 
9.3%
Uppercase Letter54
 
8.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a161
28.7%
r80
14.3%
p66
11.8%
i37
 
6.6%
s33
 
5.9%
ó33
 
5.9%
u28
 
5.0%
l28
 
5.0%
g28
 
5.0%
e21
 
3.8%
Other values (6)45
 
8.0%
Uppercase Letter
ValueCountFrequency (%)
C33
61.1%
P14
25.9%
M7
 
13.0%
Space Separator
ValueCountFrequency (%)
63
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin614
90.7%
Common63
 
9.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a161
26.2%
r80
13.0%
p66
10.7%
i37
 
6.0%
C33
 
5.4%
s33
 
5.4%
ó33
 
5.4%
u28
 
4.6%
l28
 
4.6%
g28
 
4.6%
Other values (9)87
14.2%
Common
ValueCountFrequency (%)
63
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII644
95.1%
None33
 
4.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a161
25.0%
r80
12.4%
p66
10.2%
63
 
9.8%
i37
 
5.7%
C33
 
5.1%
s33
 
5.1%
u28
 
4.3%
l28
 
4.3%
g28
 
4.3%
Other values (9)87
13.5%
None
ValueCountFrequency (%)
ó33
100.0%

eletrcs
Categorical

HIGH CORRELATION
MISSING

Distinct33
Distinct (%)61.1%
Missing3
Missing (%)5.3%
Memory size584.0 B
Computador Geladeira Fogão Microondas Televisão Ar condicionado Máquina de lavar roupa Celular Rádio
Geladeira Fogão Televisão Máquina de lavar roupa Celular
Geladeira Fogão Televisão Máquina de lavar roupa Celular Rádio
 
3
Geladeira Fogão Televisão Celular Rádio
 
3
Geladeira Fogão Televisão Ar condicionado Máquina de lavar roupa Celular
 
3
Other values (28)
34 

Length

Max length104
Median length73
Mean length62.5
Min length9

Characters and Unicode

Total characters3375
Distinct characters33
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)40.7%

Sample

1st rowGeladeira Fogão Celular
2nd rowFogão Celular
3rd rowGeladeira Fogão Microondas Televisão Máquina de lavar roupa
4th rowGeladeira Fogão Televisão Máquina de lavar roupa Celular Rádio
5th rowComputador Geladeira Fogão Microondas Televisão Ar condicionado Máquina de lavar roupa Celular Rádio

Common Values

ValueCountFrequency (%)
Computador Geladeira Fogão Microondas Televisão Ar condicionado Máquina de lavar roupa Celular Rádio6
 
10.5%
Geladeira Fogão Televisão Máquina de lavar roupa Celular5
 
8.8%
Geladeira Fogão Televisão Máquina de lavar roupa Celular Rádio3
 
5.3%
Geladeira Fogão Televisão Celular Rádio3
 
5.3%
Geladeira Fogão Televisão Ar condicionado Máquina de lavar roupa Celular3
 
5.3%
Computador Geladeira Fogão Televisão Ar condicionado Celular2
 
3.5%
Geladeira Fogão Microondas Televisão Ar condicionado Celular Rádio2
 
3.5%
Geladeira Fogão Microondas Televisão Ar condicionado Máquina de lavar roupa Celular Rádio2
 
3.5%
Geladeira2
 
3.5%
Geladeira Fogão Televisão Celular2
 
3.5%
Other values (23)24
42.1%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:27.627950image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
fogão50
11.2%
geladeira50
11.2%
celular50
11.2%
televisão48
10.8%
roupa32
7.2%
máquina32
7.2%
de32
7.2%
lavar32
7.2%
rádio27
 
6.1%
microondas23
 
5.2%
Other values (10)70
15.7%

Most occurring characters

ValueCountFrequency (%)
392
11.6%
o362
10.7%
a343
 
10.2%
e280
 
8.3%
l233
 
6.9%
r231
 
6.8%
i230
 
6.8%
d195
 
5.8%
u130
 
3.9%
n105
 
3.1%
Other values (23)874
25.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2659
78.8%
Space Separator392
 
11.6%
Uppercase Letter324
 
9.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o362
13.6%
a343
12.9%
e280
10.5%
l233
8.8%
r231
8.7%
i230
8.6%
d195
7.3%
u130
 
4.9%
n105
 
3.9%
ã98
 
3.7%
Other values (13)452
17.0%
Uppercase Letter
ValueCountFrequency (%)
C67
20.7%
M55
17.0%
F51
15.7%
G50
15.4%
T49
15.1%
R27
8.3%
A23
 
7.1%
V1
 
0.3%
E1
 
0.3%
Space Separator
ValueCountFrequency (%)
392
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2983
88.4%
Common392
 
11.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
o362
12.1%
a343
11.5%
e280
 
9.4%
l233
 
7.8%
r231
 
7.7%
i230
 
7.7%
d195
 
6.5%
u130
 
4.4%
n105
 
3.5%
ã98
 
3.3%
Other values (22)776
26.0%
Common
ValueCountFrequency (%)
392
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3216
95.3%
None159
 
4.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
392
12.2%
o362
11.3%
a343
10.7%
e280
 
8.7%
l233
 
7.2%
r231
 
7.2%
i230
 
7.2%
d195
 
6.1%
u130
 
4.0%
n105
 
3.3%
Other values (20)715
22.2%
None
ValueCountFrequency (%)
ã98
61.6%
á59
37.1%
é2
 
1.3%

dormecs
Categorical

HIGH CORRELATION
MISSING

Distinct5
Distinct (%)9.4%
Missing4
Missing (%)7.0%
Memory size584.0 B
Durmo num cômodo sozinho em cama/colchão/outros sozinho
32 
Durmo num cômodo com mais pessoas, porém em uma cama/colchão/outros só minha
10 
Durmo num cômodo com mais pessoas e divido cama/colchão/outros
Durmo num cômodo sozinho sem cama/colchão/outros
LVAr+4t4Dmbgg5BO0bG/D5LDxwyhO+ulXz9dftbVIyxOwUDwhDz1szBaoftK/mZ8wP5Kd/10LFeglrqbQJ1TsMk4AUG+LId41HOwpTGhWWfBLxXOtvyplnvLHKAeFg7Jqq9qX7D+E5s31u9lDJgtHzwKFfVg2Cy2ZpWSNPrn4YFnbhqGeM9fCi55TYzhpDDjswiTg8dCNDpirPLism1lQYPS9GrA95PbRc/F+ZpUEW6ezo+U5P+5NKNSXuEPTjcMTM78FO4iyvCdGSMYGy7x2q7gbNHpTyQaX/emmoi5UQUiY3RIVDRprx3oo8/rpYlKtkfcJjLYuHE0RTrUoZ5cdg==#Jot#L1ArxiBhCmyYwAafEVQ5eqLtq/KOFjvFtuIgcJjpUq2BX+cmAEg0fOsNG/xMpqyUJmCIeIXguFCVA7fYutARqFGnUcjQfbahHazLL2JNrJwJHUm8A4/u0QEwHRBlqDLRztmx2ygphMcIXieeWrDWrNFfYhcvOURwxBx8B3bh6VSA6xIMMZhAtyI2/3cW0GMMR1ugzyz6KAJ5oQibZmQDGrmr8rxmDLo1k7gbxR99E8Stsvny75pRgChSn1qQvxhw2FY3i4bh2XD5HZWzF99bW8yWKBVcxjXNv8foGZXpJd9cLMgA3C1OjyrSoNPsimb7so/SeSXwEzQl2NvJ+6u0Ew==#Jot#BrR4pcfNXZNC+Or4Get36ilStWqXLSNOkTg8YgNWutwy1gG0J+7trqAIJq4//QjSiMfIUwzfmj7/O4pM95itQE45oziy0JJvTYbD5OI+6vTxqPKLLFXD+S622/lyY+lBCCvqCjwFaGSGFBYe5j2enBK70Sa3f9UsMAWRDaN9emIy83QpCECope1AJWWWbBfGLyfU0VMjYHaBuPlXO26vNEa2786cbPPAGs/bG+qaqD2UHG1ZSjXWIAfcxRd2BOpcjREMt3a83xMfZMBBMaMpGOOQXfNR97HUW4u2b6fPIQnn5rbHEqT/mjzMGvzsa1rqBnXM+Aukmp/tBR/o79VAKA==#Jot#IG6ruPLoc7cHycldeqJIERUBtBXwp2INY8XUeqhbm8SgNZW9LjnhtUBjr5ODMrpvobCTo8MRohWPbKkKXYhts/Cg+/cFlu9PbNLlgOAJZ1H1T/YYz1L+0LYiGFe7DM9Gry4M9/rRFPV2R0AWurJIkL9SkWaLqYHdzk7iTAs3cIXt2eU7Bhcx1OVA0RHKKEncqJl17wgsEq9AuJnOp6acDKRRJo6jP7LxeisiUZ4+73xOHFMvZ456claoN0C5MsQoVHBi140T1QiG+KDS5lO9OT1rQigrjH27xygLQkONf8Csn0ll99AWVWcn3+Hjz8+zw7sSA+1lPsy8YiBn1FTE1A==#Jot#NZZ+LHJDpgSct6vcvBq2Lc5TFMif7Et55Z4WSK29JYEedKKu0ovMVVOZAECsI+UW3rk1w4H89vpka5396vFzAYacXQcLAVuQV3LBzu9HFzBfkmynS5QnFJFb4XThsc6ZIStn9ap6z83VFHenBXxvuy/TMa/JtDfNH48FJnDEmM8BmrN7Aw7s+3gyJO0kqV/NI2iCdLFdZTXGbP+ocovo1caGgvs/hbPIzF7L2z0Jla4UdtZwyPZZat5hb9Ic10AhfVL0x6tEvR7wCbA4sJ6AUAo9wQvHrrt2/LkSTwJU8ZEHiM8xEIGFAuRMkQwEsVvdqRheE6oV2lCAYf6EYBL4mA==#Jot#W+EDKUQaJI0ovPHXyRCDcQOi8s8+PehH/Ou4/Yz8TbXn+pQrbhADMNy9V3kSoT4px9TYG0vveIAhnHJXsfkft3QNSnzbVFRF3vPvtjVNp8gxDSzLXhB7EB9WEeD6nqPpZX4v8Lz0h4egcPgySxyiQ8RrrE0lQxCxrWI40vcZsRWI/PhgTHP2w/Tp8cqChsxjotJNLcHMr/DGERdKCRLBmYDxw4hDC5mSD24TITG7pzqY1qdOEBPNwbkyM1Czz8A8m10OxSW/uT5BO/8f6W9i3s8/VfJ8+EArGbN1M4IS5fwwN+WTI/RW1X3oil/QlMYpGhtt/FCiXVJpufcsAtsd+g==#Jot#c/hdfTZ+lXSKFVfrzEhKqnnVfFAGSJ1jMEvEbJxVCRZ4fSoOv9lGBC+kJ50AKfNx7p2ewlR383QadexUGKouMDxFOlm5CpRY0KbdE5/IJd+vZ3RA+2BRalgDt8SNw+gxoe3eDJ/Wwq3DjKjS8R7avoGKvzwNIwM3qQ6THte5BkzWk8VunvHPAl4gwD+EsPHuZ/iY+UMPCO8ZqYg9fAyOLDRL3pxQhyWeU+nIKHWKWatzRs1FU4yDOiVDse5Yh54OjzQxFSQniVQa5s3MGp7JKhlTX/eNOBMCMrA08Psa3t4gor4vkag2xRK6wPNWyiRzmtGy3CHuHNL/xn62X8gL2g==
 
1

Length

Max length2438
Median length55
Mean length103.9245283
Min length48

Characters and Unicode

Total characters5508
Distinct characters72
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st rowDurmo num cômodo sozinho em cama/colchão/outros sozinho
2nd rowDurmo num cômodo sozinho em cama/colchão/outros sozinho
3rd rowDurmo num cômodo com mais pessoas e divido cama/colchão/outros
4th rowDurmo num cômodo sozinho em cama/colchão/outros sozinho
5th rowDurmo num cômodo com mais pessoas, porém em uma cama/colchão/outros só minha

Common Values

ValueCountFrequency (%)
Durmo num cômodo sozinho em cama/colchão/outros sozinho32
56.1%
Durmo num cômodo com mais pessoas, porém em uma cama/colchão/outros só minha10
 
17.5%
Durmo num cômodo com mais pessoas e divido cama/colchão/outros5
 
8.8%
Durmo num cômodo sozinho sem cama/colchão/outros5
 
8.8%
LVAr+4t4Dmbgg5BO0bG/D5LDxwyhO+ulXz9dftbVIyxOwUDwhDz1szBaoftK/mZ8wP5Kd/10LFeglrqbQJ1TsMk4AUG+LId41HOwpTGhWWfBLxXOtvyplnvLHKAeFg7Jqq9qX7D+E5s31u9lDJgtHzwKFfVg2Cy2ZpWSNPrn4YFnbhqGeM9fCi55TYzhpDDjswiTg8dCNDpirPLism1lQYPS9GrA95PbRc/F+ZpUEW6ezo+U5P+5NKNSXuEPTjcMTM78FO4iyvCdGSMYGy7x2q7gbNHpTyQaX/emmoi5UQUiY3RIVDRprx3oo8/rpYlKtkfcJjLYuHE0RTrUoZ5cdg==#Jot#L1ArxiBhCmyYwAafEVQ5eqLtq/KOFjvFtuIgcJjpUq2BX+cmAEg0fOsNG/xMpqyUJmCIeIXguFCVA7fYutARqFGnUcjQfbahHazLL2JNrJwJHUm8A4/u0QEwHRBlqDLRztmx2ygphMcIXieeWrDWrNFfYhcvOURwxBx8B3bh6VSA6xIMMZhAtyI2/3cW0GMMR1ugzyz6KAJ5oQibZmQDGrmr8rxmDLo1k7gbxR99E8Stsvny75pRgChSn1qQvxhw2FY3i4bh2XD5HZWzF99bW8yWKBVcxjXNv8foGZXpJd9cLMgA3C1OjyrSoNPsimb7so/SeSXwEzQl2NvJ+6u0Ew==#Jot#BrR4pcfNXZNC+Or4Get36ilStWqXLSNOkTg8YgNWutwy1gG0J+7trqAIJq4//QjSiMfIUwzfmj7/O4pM95itQE45oziy0JJvTYbD5OI+6vTxqPKLLFXD+S622/lyY+lBCCvqCjwFaGSGFBYe5j2enBK70Sa3f9UsMAWRDaN9emIy83QpCECope1AJWWWbBfGLyfU0VMjYHaBuPlXO26vNEa2786cbPPAGs/bG+qaqD2UHG1ZSjXWIAfcxRd2BOpcjREMt3a83xMfZMBBMaMpGOOQXfNR97HUW4u2b6fPIQnn5rbHEqT/mjzMGvzsa1rqBnXM+Aukmp/tBR/o79VAKA==#Jot#IG6ruPLoc7cHycldeqJIERUBtBXwp2INY8XUeqhbm8SgNZW9LjnhtUBjr5ODMrpvobCTo8MRohWPbKkKXYhts/Cg+/cFlu9PbNLlgOAJZ1H1T/YYz1L+0LYiGFe7DM9Gry4M9/rRFPV2R0AWurJIkL9SkWaLqYHdzk7iTAs3cIXt2eU7Bhcx1OVA0RHKKEncqJl17wgsEq9AuJnOp6acDKRRJo6jP7LxeisiUZ4+73xOHFMvZ456claoN0C5MsQoVHBi140T1QiG+KDS5lO9OT1rQigrjH27xygLQkONf8Csn0ll99AWVWcn3+Hjz8+zw7sSA+1lPsy8YiBn1FTE1A==#Jot#NZZ+LHJDpgSct6vcvBq2Lc5TFMif7Et55Z4WSK29JYEedKKu0ovMVVOZAECsI+UW3rk1w4H89vpka5396vFzAYacXQcLAVuQV3LBzu9HFzBfkmynS5QnFJFb4XThsc6ZIStn9ap6z83VFHenBXxvuy/TMa/JtDfNH48FJnDEmM8BmrN7Aw7s+3gyJO0kqV/NI2iCdLFdZTXGbP+ocovo1caGgvs/hbPIzF7L2z0Jla4UdtZwyPZZat5hb9Ic10AhfVL0x6tEvR7wCbA4sJ6AUAo9wQvHrrt2/LkSTwJU8ZEHiM8xEIGFAuRMkQwEsVvdqRheE6oV2lCAYf6EYBL4mA==#Jot#W+EDKUQaJI0ovPHXyRCDcQOi8s8+PehH/Ou4/Yz8TbXn+pQrbhADMNy9V3kSoT4px9TYG0vveIAhnHJXsfkft3QNSnzbVFRF3vPvtjVNp8gxDSzLXhB7EB9WEeD6nqPpZX4v8Lz0h4egcPgySxyiQ8RrrE0lQxCxrWI40vcZsRWI/PhgTHP2w/Tp8cqChsxjotJNLcHMr/DGERdKCRLBmYDxw4hDC5mSD24TITG7pzqY1qdOEBPNwbkyM1Czz8A8m10OxSW/uT5BO/8f6W9i3s8/VfJ8+EArGbN1M4IS5fwwN+WTI/RW1X3oil/QlMYpGhtt/FCiXVJpufcsAtsd+g==#Jot#c/hdfTZ+lXSKFVfrzEhKqnnVfFAGSJ1jMEvEbJxVCRZ4fSoOv9lGBC+kJ50AKfNx7p2ewlR383QadexUGKouMDxFOlm5CpRY0KbdE5/IJd+vZ3RA+2BRalgDt8SNw+gxoe3eDJ/Wwq3DjKjS8R7avoGKvzwNIwM3qQ6THte5BkzWk8VunvHPAl4gwD+EsPHuZ/iY+UMPCO8ZqYg9fAyOLDRL3pxQhyWeU+nIKHWKWatzRs1FU4yDOiVDse5Yh54OjzQxFSQniVQa5s3MGp7JKhlTX/eNOBMCMrA08Psa3t4gor4vkag2xRK6wPNWyiRzmtGy3CHuHNL/xn62X8gL2g==1
 
1.8%
(Missing)4
 
7.0%

Length

2022-05-31T15:05:27.745767image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:27.958964image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sozinho69
16.4%
durmo52
12.4%
cômodo52
12.4%
cama/colchão/outros52
12.4%
num52
12.4%
em42
10.0%
mais15
 
3.6%
pessoas15
 
3.6%
com15
 
3.6%
porém10
 
2.4%
Other values (7)46
11.0%

Most occurring characters

ValueCountFrequency (%)
o589
 
10.7%
367
 
6.7%
m343
 
6.2%
c265
 
4.8%
s234
 
4.2%
u196
 
3.6%
a186
 
3.4%
h169
 
3.1%
n162
 
2.9%
r156
 
2.8%
Other values (62)2841
51.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3478
63.1%
Uppercase Letter1076
 
19.5%
Space Separator367
 
6.7%
Decimal Number361
 
6.6%
Other Punctuation171
 
3.1%
Math Symbol55
 
1.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o589
16.9%
m343
 
9.9%
c265
 
7.6%
s234
 
6.7%
u196
 
5.6%
a186
 
5.3%
h169
 
4.9%
n162
 
4.7%
r156
 
4.5%
i140
 
4.0%
Other values (20)1038
29.8%
Uppercase Letter
ValueCountFrequency (%)
D96
 
8.9%
A52
 
4.8%
J49
 
4.6%
M47
 
4.4%
L45
 
4.2%
R44
 
4.1%
E41
 
3.8%
B41
 
3.8%
N40
 
3.7%
W40
 
3.7%
Other values (16)581
54.0%
Decimal Number
ValueCountFrequency (%)
845
12.5%
540
11.1%
439
10.8%
938
10.5%
136
10.0%
235
9.7%
335
9.7%
734
9.4%
031
8.6%
628
7.8%
Other Punctuation
ValueCountFrequency (%)
/149
87.1%
#12
 
7.0%
,10
 
5.8%
Math Symbol
ValueCountFrequency (%)
+41
74.5%
=14
 
25.5%
Space Separator
ValueCountFrequency (%)
367
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4554
82.7%
Common954
 
17.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o589
 
12.9%
m343
 
7.5%
c265
 
5.8%
s234
 
5.1%
u196
 
4.3%
a186
 
4.1%
h169
 
3.7%
n162
 
3.6%
r156
 
3.4%
i140
 
3.1%
Other values (46)2114
46.4%
Common
ValueCountFrequency (%)
367
38.5%
/149
15.6%
845
 
4.7%
+41
 
4.3%
540
 
4.2%
439
 
4.1%
938
 
4.0%
136
 
3.8%
235
 
3.7%
335
 
3.7%
Other values (6)129
 
13.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII5384
97.7%
None124
 
2.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o589
 
10.9%
367
 
6.8%
m343
 
6.4%
c265
 
4.9%
s234
 
4.3%
u196
 
3.6%
a186
 
3.5%
h169
 
3.1%
n162
 
3.0%
r156
 
2.9%
Other values (58)2717
50.5%
None
ValueCountFrequency (%)
ã52
41.9%
ô52
41.9%
ó10
 
8.1%
é10
 
8.1%

comunservs
Categorical

HIGH CORRELATION
MISSING

Distinct24
Distinct (%)44.4%
Missing3
Missing (%)5.3%
Memory size584.0 B
Fornecimento de energia elétrica Água encanada Sistema de esgoto Coleta de lixo Escola/creche pública Escola/creche privada Posto de atendimento médico
22 
Não sei dizer
Fornecimento de energia elétrica Água encanada Escola/creche pública Posto de atendimento médico
Fornecimento de energia elétrica Água encanada Sistema de esgoto Coleta de lixo Escola/creche pública Posto de atendimento médico
 
2
Fornecimento de energia elétrica Água encanada
 
2
Other values (19)
21 

Length

Max length169
Median length136
Mean length111.2037037
Min length13

Characters and Unicode

Total characters6005
Distinct characters34
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)31.5%

Sample

1st rowPosto de atendimento médico
2nd rowNão sei dizer
3rd rowEscola/creche pública Escola/creche privada
4th rowFornecimento de energia elétrica Água encanada
5th rowSistema de esgoto Coleta de lixo

Common Values

ValueCountFrequency (%)
Fornecimento de energia elétrica Água encanada Sistema de esgoto Coleta de lixo Escola/creche pública Escola/creche privada Posto de atendimento médico22
38.6%
Não sei dizer4
 
7.0%
Fornecimento de energia elétrica Água encanada Escola/creche pública Posto de atendimento médico3
 
5.3%
Fornecimento de energia elétrica Água encanada Sistema de esgoto Coleta de lixo Escola/creche pública Posto de atendimento médico2
 
3.5%
Fornecimento de energia elétrica Água encanada2
 
3.5%
Fornecimento de energia elétrica Água encanada Escola/creche pública Escola/creche privada2
 
3.5%
Fornecimento de energia elétrica Água encanada Sistema de esgoto Coleta de lixo Escola/creche pública Escola/creche privada Posto de atendimento médico Horta comunitária2
 
3.5%
Fornecimento de energia elétrica Coleta de lixo Escola/creche pública Escola/creche privada Posto de atendimento médico1
 
1.8%
Água encanada Coleta de lixo Escola/creche pública Posto de atendimento médico1
 
1.8%
Água encanada Sistema de esgoto Coleta de lixo Escola/creche pública Escola/creche privada Posto de atendimento médico Horta comunitária1
 
1.8%
Other values (14)14
24.6%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:28.667190image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
de152
19.0%
escola/creche74
 
9.3%
encanada44
 
5.5%
água44
 
5.5%
pública42
 
5.3%
fornecimento42
 
5.3%
elétrica42
 
5.3%
energia42
 
5.3%
posto40
 
5.0%
atendimento40
 
5.0%
Other values (11)237
29.7%

Most occurring characters

ValueCountFrequency (%)
e747
12.4%
745
12.4%
a560
 
9.3%
o473
 
7.9%
c437
 
7.3%
i370
 
6.2%
t317
 
5.3%
d313
 
5.2%
n299
 
5.0%
r247
 
4.1%
Other values (24)1497
24.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4906
81.7%
Space Separator745
 
12.4%
Uppercase Letter280
 
4.7%
Other Punctuation74
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e747
15.2%
a560
11.4%
o473
9.6%
c437
8.9%
i370
7.5%
t317
 
6.5%
d313
 
6.4%
n299
 
6.1%
r247
 
5.0%
l232
 
4.7%
Other values (14)911
18.6%
Uppercase Letter
ValueCountFrequency (%)
E74
26.4%
Á44
15.7%
F42
15.0%
P40
14.3%
C37
13.2%
S33
11.8%
N5
 
1.8%
H5
 
1.8%
Space Separator
ValueCountFrequency (%)
745
100.0%
Other Punctuation
ValueCountFrequency (%)
/74
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5186
86.4%
Common819
 
13.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e747
14.4%
a560
10.8%
o473
 
9.1%
c437
 
8.4%
i370
 
7.1%
t317
 
6.1%
d313
 
6.0%
n299
 
5.8%
r247
 
4.8%
l232
 
4.5%
Other values (22)1191
23.0%
Common
ValueCountFrequency (%)
745
91.0%
/74
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII5827
97.0%
None178
 
3.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e747
12.8%
745
12.8%
a560
9.6%
o473
 
8.1%
c437
 
7.5%
i370
 
6.3%
t317
 
5.4%
d313
 
5.4%
n299
 
5.1%
r247
 
4.2%
Other values (19)1319
22.6%
None
ValueCountFrequency (%)
é82
46.1%
Á44
24.7%
ú42
23.6%
ã5
 
2.8%
á5
 
2.8%

vias
Categorical

HIGH CORRELATION
MISSING

Distinct6
Distinct (%)11.1%
Missing3
Missing (%)5.3%
Memory size584.0 B
Rua asfaltada
42 
Rua e terra
Terra/chão batido
 
4
Rua de pedra
 
1
ALFATO E TERRA
 
1

Length

Max length26
Median length13
Mean length13.35185185
Min length11

Characters and Unicode

Total characters721
Distinct characters27
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)5.6%

Sample

1st rowTerra/chão batido
2nd rowRua asfaltada
3rd rowRua de pedra
4th rowRua asfaltada
5th rowRua asfaltada

Common Values

ValueCountFrequency (%)
Rua asfaltada42
73.7%
Rua e terra5
 
8.8%
Terra/chão batido4
 
7.0%
Rua de pedra1
 
1.8%
ALFATO E TERRA1
 
1.8%
Parte asfalto, parte barro1
 
1.8%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:28.823301image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:28.999830image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
rua48
41.0%
asfaltada42
35.9%
e6
 
5.1%
terra6
 
5.1%
terra/chão4
 
3.4%
batido4
 
3.4%
parte2
 
1.7%
de1
 
0.9%
pedra1
 
0.9%
alfato1
 
0.9%
Other values (2)2
 
1.7%

Most occurring characters

ValueCountFrequency (%)
a235
32.6%
63
 
8.7%
t54
 
7.5%
R50
 
6.9%
d48
 
6.7%
u48
 
6.7%
s43
 
6.0%
f43
 
6.0%
l43
 
6.0%
r23
 
3.2%
Other values (17)71
 
9.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter588
81.6%
Uppercase Letter65
 
9.0%
Space Separator63
 
8.7%
Other Punctuation5
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a235
40.0%
t54
 
9.2%
d48
 
8.2%
u48
 
8.2%
s43
 
7.3%
f43
 
7.3%
l43
 
7.3%
r23
 
3.9%
e18
 
3.1%
o10
 
1.7%
Other values (6)23
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
R50
76.9%
T6
 
9.2%
A3
 
4.6%
E2
 
3.1%
L1
 
1.5%
F1
 
1.5%
O1
 
1.5%
P1
 
1.5%
Other Punctuation
ValueCountFrequency (%)
/4
80.0%
,1
 
20.0%
Space Separator
ValueCountFrequency (%)
63
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin653
90.6%
Common68
 
9.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a235
36.0%
t54
 
8.3%
R50
 
7.7%
d48
 
7.4%
u48
 
7.4%
s43
 
6.6%
f43
 
6.6%
l43
 
6.6%
r23
 
3.5%
e18
 
2.8%
Other values (14)48
 
7.4%
Common
ValueCountFrequency (%)
63
92.6%
/4
 
5.9%
,1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII717
99.4%
None4
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a235
32.8%
63
 
8.8%
t54
 
7.5%
R50
 
7.0%
d48
 
6.7%
u48
 
6.7%
s43
 
6.0%
f43
 
6.0%
l43
 
6.0%
r23
 
3.2%
Other values (16)67
 
9.3%
None
ValueCountFrequency (%)
ã4
100.0%

espcscomn
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct42
Distinct (%)79.2%
Missing4
Missing (%)7.0%
Memory size584.0 B
Praça pública Quadra de futebol Quadra poliesportiva Espaço cultural Parque infantil Parque arborizado Centro comunitário Espaço de eventos e lazer Bailes e fluxos (funk, forró, reggae, rap, rock etc)
 
4
Praça pública Quadra de futebol Bailes e fluxos (funk, forró, reggae, rap, rock etc)
 
2
Praça pública Quadra de futebol Quadra poliesportiva Centro comunitário
 
2
Praça pública Quadra de futebol Quadra poliesportiva Espaço cultural Parque arborizado Centro comunitário Espaço de eventos e lazer Bailes e fluxos (funk, forró, reggae, rap, rock etc)
 
2
Praça pública Quadra de futebol Quadra poliesportiva Espaço cultural Parque infantil Centro comunitário Espaço de eventos e lazer Bailes e fluxos (funk, forró, reggae, rap, rock etc)
 
2
Other values (37)
41 

Length

Max length200
Median length145
Mean length123.3018868
Min length13

Characters and Unicode

Total characters6535
Distinct characters35
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)62.3%

Sample

1st rowEspaço cultural
2nd rowPraça pública Quadra de futebol Quadra poliesportiva Espaço cultural Parque infantil Parque arborizado Centro comunitário Espaço de eventos e lazer Bailes e fluxos (funk, forró, reggae, rap, rock etc)
3rd rowPraça pública Quadra de futebol Quadra poliesportiva Parque infantil Bailes e fluxos (funk, forró, reggae, rap, rock etc)
4th rowPraça pública Quadra de futebol Espaço cultural Parque infantil Parque arborizado Centro comunitário Espaço de eventos e lazer Bailes e fluxos (funk, forró, reggae, rap, rock etc)
5th rowPraça pública Quadra de futebol Espaço cultural Parque infantil Bailes e fluxos (funk, forró, reggae, rap, rock etc)

Common Values

ValueCountFrequency (%)
Praça pública Quadra de futebol Quadra poliesportiva Espaço cultural Parque infantil Parque arborizado Centro comunitário Espaço de eventos e lazer Bailes e fluxos (funk, forró, reggae, rap, rock etc)4
 
7.0%
Praça pública Quadra de futebol Bailes e fluxos (funk, forró, reggae, rap, rock etc)2
 
3.5%
Praça pública Quadra de futebol Quadra poliesportiva Centro comunitário2
 
3.5%
Praça pública Quadra de futebol Quadra poliesportiva Espaço cultural Parque arborizado Centro comunitário Espaço de eventos e lazer Bailes e fluxos (funk, forró, reggae, rap, rock etc)2
 
3.5%
Praça pública Quadra de futebol Quadra poliesportiva Espaço cultural Parque infantil Centro comunitário Espaço de eventos e lazer Bailes e fluxos (funk, forró, reggae, rap, rock etc)2
 
3.5%
Praça pública Quadra de futebol Quadra poliesportiva Espaço cultural Centro comunitário Espaço de eventos e lazer Bailes e fluxos (funk, forró, reggae, rap, rock etc)2
 
3.5%
Praça pública Quadra de futebol Centro comunitário Espaço de eventos e lazer Bailes e fluxos (funk, forró, reggae, rap, rock etc)2
 
3.5%
Praça pública Quadra de futebol Quadra poliesportiva Parque infantil Bailes e fluxos (funk, forró, reggae, rap, rock etc)2
 
3.5%
Praça pública Quadra de futebol Quadra poliesportiva Espaço cultural Parque infantil Parque arborizado Bailes e fluxos (funk, forró, reggae, rap, rock etc)2
 
3.5%
Praça pública Bailes e fluxos (funk, forró, reggae, rap, rock etc)1
 
1.8%
Other values (32)32
56.1%
(Missing)4
 
7.0%

Length

2022-05-31T15:05:29.157408image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
quadra71
 
7.2%
de70
 
7.1%
e66
 
6.7%
espaço55
 
5.6%
praça48
 
4.9%
pública48
 
4.9%
futebol46
 
4.7%
rock42
 
4.3%
rap42
 
4.3%
reggae42
 
4.3%
Other values (14)452
46.0%

Most occurring characters

ValueCountFrequency (%)
929
14.2%
a647
 
9.9%
r537
 
8.2%
e516
 
7.9%
o414
 
6.3%
u332
 
5.1%
l315
 
4.8%
i262
 
4.0%
t248
 
3.8%
f198
 
3.0%
Other values (25)2137
32.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5069
77.6%
Space Separator929
 
14.2%
Uppercase Letter285
 
4.4%
Other Punctuation168
 
2.6%
Open Punctuation42
 
0.6%
Close Punctuation42
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a647
12.8%
r537
 
10.6%
e516
 
10.2%
o414
 
8.2%
u332
 
6.5%
l315
 
6.2%
i262
 
5.2%
t248
 
4.9%
f198
 
3.9%
p195
 
3.8%
Other values (16)1405
27.7%
Uppercase Letter
ValueCountFrequency (%)
P90
31.6%
Q71
24.9%
E55
19.3%
B42
14.7%
C27
 
9.5%
Space Separator
ValueCountFrequency (%)
929
100.0%
Other Punctuation
ValueCountFrequency (%)
,168
100.0%
Open Punctuation
ValueCountFrequency (%)
(42
100.0%
Close Punctuation
ValueCountFrequency (%)
)42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5354
81.9%
Common1181
 
18.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a647
 
12.1%
r537
 
10.0%
e516
 
9.6%
o414
 
7.7%
u332
 
6.2%
l315
 
5.9%
i262
 
4.9%
t248
 
4.6%
f198
 
3.7%
p195
 
3.6%
Other values (21)1690
31.6%
Common
ValueCountFrequency (%)
929
78.7%
,168
 
14.2%
(42
 
3.6%
)42
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII6315
96.6%
None220
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
929
14.7%
a647
 
10.2%
r537
 
8.5%
e516
 
8.2%
o414
 
6.6%
u332
 
5.3%
l315
 
5.0%
i262
 
4.1%
t248
 
3.9%
f198
 
3.1%
Other values (21)1917
30.4%
None
ValueCountFrequency (%)
ç103
46.8%
ú48
21.8%
ó42
19.1%
á27
 
12.3%

cartass
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)3.7%
Missing3
Missing (%)5.3%
Memory size584.0 B
Sim
28 
Não
26 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters162
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão
2nd rowNão
3rd rowNão
4th rowNão
5th rowNão

Common Values

ValueCountFrequency (%)
Sim28
49.1%
Não26
45.6%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:29.291621image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:29.398305image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim28
51.9%
não26
48.1%

Most occurring characters

ValueCountFrequency (%)
S28
17.3%
i28
17.3%
m28
17.3%
N26
16.0%
ã26
16.0%
o26
16.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter108
66.7%
Uppercase Letter54
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i28
25.9%
m28
25.9%
ã26
24.1%
o26
24.1%
Uppercase Letter
ValueCountFrequency (%)
S28
51.9%
N26
48.1%

Most occurring scripts

ValueCountFrequency (%)
Latin162
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S28
17.3%
i28
17.3%
m28
17.3%
N26
16.0%
ã26
16.0%
o26
16.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII136
84.0%
None26
 
16.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S28
20.6%
i28
20.6%
m28
20.6%
N26
19.1%
o26
19.1%
None
ValueCountFrequency (%)
ã26
100.0%

empatual
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)7.4%
Missing3
Missing (%)5.3%
Memory size584.0 B
Estou desempregado
25 
Sou trabalhador informal (MEI, bico, freelancer)
16 
Estou empregado
Nunca trabalhei

Length

Max length48
Median length18
Mean length26.16666667
Min length15

Characters and Unicode

Total characters1413
Distinct characters27
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNunca trabalhei
2nd rowEstou desempregado
3rd rowNunca trabalhei
4th rowEstou empregado
5th rowEstou desempregado

Common Values

ValueCountFrequency (%)
Estou desempregado25
43.9%
Sou trabalhador informal (MEI, bico, freelancer)16
28.1%
Estou empregado9
 
15.8%
Nunca trabalhei4
 
7.0%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:30.058693image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:30.208260image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
estou34
19.8%
desempregado25
14.5%
sou16
9.3%
trabalhador16
9.3%
informal16
9.3%
mei16
9.3%
bico16
9.3%
freelancer16
9.3%
empregado9
 
5.2%
nunca4
 
2.3%

Most occurring characters

ValueCountFrequency (%)
e145
 
10.3%
o132
 
9.3%
a126
 
8.9%
118
 
8.4%
r118
 
8.4%
d75
 
5.3%
s59
 
4.2%
t54
 
3.8%
u54
 
3.8%
l52
 
3.7%
Other values (17)480
34.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1129
79.9%
Space Separator118
 
8.4%
Uppercase Letter102
 
7.2%
Other Punctuation32
 
2.3%
Close Punctuation16
 
1.1%
Open Punctuation16
 
1.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e145
12.8%
o132
11.7%
a126
11.2%
r118
10.5%
d75
 
6.6%
s59
 
5.2%
t54
 
4.8%
u54
 
4.8%
l52
 
4.6%
m50
 
4.4%
Other values (8)264
23.4%
Uppercase Letter
ValueCountFrequency (%)
E50
49.0%
S16
 
15.7%
I16
 
15.7%
M16
 
15.7%
N4
 
3.9%
Space Separator
ValueCountFrequency (%)
118
100.0%
Other Punctuation
ValueCountFrequency (%)
,32
100.0%
Close Punctuation
ValueCountFrequency (%)
)16
100.0%
Open Punctuation
ValueCountFrequency (%)
(16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1231
87.1%
Common182
 
12.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e145
 
11.8%
o132
 
10.7%
a126
 
10.2%
r118
 
9.6%
d75
 
6.1%
s59
 
4.8%
t54
 
4.4%
u54
 
4.4%
l52
 
4.2%
E50
 
4.1%
Other values (13)366
29.7%
Common
ValueCountFrequency (%)
118
64.8%
,32
 
17.6%
)16
 
8.8%
(16
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII1413
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e145
 
10.3%
o132
 
9.3%
a126
 
8.9%
118
 
8.4%
r118
 
8.4%
d75
 
5.3%
s59
 
4.2%
t54
 
3.8%
u54
 
3.8%
l52
 
3.7%
Other values (17)480
34.0%

trabcomn
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)6.8%
Missing13
Missing (%)22.8%
Memory size584.0 B
Não, mas trabalho longe
20 
Sim
15 
Não, mas trabalho perto

Length

Max length23
Median length23
Mean length16.18181818
Min length3

Characters and Unicode

Total characters712
Distinct characters19
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão, mas trabalho longe
2nd rowSim
3rd rowSim
4th rowNão, mas trabalho longe
5th rowNão, mas trabalho longe

Common Values

ValueCountFrequency (%)
Não, mas trabalho longe20
35.1%
Sim15
26.3%
Não, mas trabalho perto9
15.8%
(Missing)13
22.8%

Length

2022-05-31T15:05:30.369828image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:30.514441image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não29
22.1%
mas29
22.1%
trabalho29
22.1%
longe20
15.3%
sim15
11.5%
perto9
 
6.9%

Most occurring characters

ValueCountFrequency (%)
o87
12.2%
87
12.2%
a87
12.2%
l49
 
6.9%
m44
 
6.2%
r38
 
5.3%
t38
 
5.3%
b29
 
4.1%
e29
 
4.1%
h29
 
4.1%
Other values (9)195
27.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter552
77.5%
Space Separator87
 
12.2%
Uppercase Letter44
 
6.2%
Other Punctuation29
 
4.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o87
15.8%
a87
15.8%
l49
8.9%
m44
8.0%
r38
6.9%
t38
6.9%
b29
 
5.3%
e29
 
5.3%
h29
 
5.3%
ã29
 
5.3%
Other values (5)93
16.8%
Uppercase Letter
ValueCountFrequency (%)
N29
65.9%
S15
34.1%
Space Separator
ValueCountFrequency (%)
87
100.0%
Other Punctuation
ValueCountFrequency (%)
,29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin596
83.7%
Common116
 
16.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o87
14.6%
a87
14.6%
l49
 
8.2%
m44
 
7.4%
r38
 
6.4%
t38
 
6.4%
b29
 
4.9%
e29
 
4.9%
h29
 
4.9%
N29
 
4.9%
Other values (7)137
23.0%
Common
ValueCountFrequency (%)
87
75.0%
,29
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII683
95.9%
None29
 
4.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o87
12.7%
87
12.7%
a87
12.7%
l49
 
7.2%
m44
 
6.4%
r38
 
5.6%
t38
 
5.6%
b29
 
4.2%
e29
 
4.2%
h29
 
4.2%
Other values (8)166
24.3%
None
ValueCountFrequency (%)
ã29
100.0%

profs
Categorical

HIGH CORRELATION
MISSING

Distinct33
Distinct (%)68.8%
Missing9
Missing (%)15.8%
Memory size584.0 B
Atendente de loja/ fastfood
Profissional do sexo
Cozinheira
Serviços gerais
 
3
Área da educação
 
2
Other values (28)
30 

Length

Max length52
Median length25
Mean length18.04166667
Min length6

Characters and Unicode

Total characters866
Distinct characters52
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)54.2%

Sample

1st rowProfissional do sexo
2nd rowCabeleireira
3rd rowCabeleireira
4th rowServiços gerais
5th rowBarreira e implantista

Common Values

ValueCountFrequency (%)
Atendente de loja/ fastfood5
 
8.8%
Profissional do sexo4
 
7.0%
Cozinheira4
 
7.0%
Serviços gerais3
 
5.3%
Área da educação2
 
3.5%
Funcionário público2
 
3.5%
Cabeleireira2
 
3.5%
trabalho informal, venda de roupas1
 
1.8%
Não trabalho1
 
1.8%
Confeiteira, Profissional do Sexo, Consultas de Jogo1
 
1.8%
Other values (23)23
40.4%
(Missing)9
 
15.8%

Length

2022-05-31T15:05:30.643095image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
de12
 
10.3%
atendente6
 
5.2%
profissional6
 
5.2%
do6
 
5.2%
loja5
 
4.3%
fastfood5
 
4.3%
sexo5
 
4.3%
cozinheira4
 
3.4%
serviços3
 
2.6%
gerais3
 
2.6%
Other values (48)61
52.6%

Most occurring characters

ValueCountFrequency (%)
e88
 
10.2%
a87
 
10.0%
o84
 
9.7%
75
 
8.7%
i68
 
7.9%
r54
 
6.2%
s51
 
5.9%
n45
 
5.2%
d45
 
5.2%
t36
 
4.2%
Other values (42)233
26.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter718
82.9%
Space Separator75
 
8.7%
Uppercase Letter64
 
7.4%
Other Punctuation9
 
1.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e88
12.3%
a87
12.1%
o84
11.7%
i68
9.5%
r54
7.5%
s51
 
7.1%
n45
 
6.3%
d45
 
6.3%
t36
 
5.0%
l32
 
4.5%
Other values (19)128
17.8%
Uppercase Letter
ValueCountFrequency (%)
A13
20.3%
C11
17.2%
P7
10.9%
S5
 
7.8%
D4
 
6.2%
F3
 
4.7%
J3
 
4.7%
M3
 
4.7%
N2
 
3.1%
Á2
 
3.1%
Other values (10)11
17.2%
Other Punctuation
ValueCountFrequency (%)
/5
55.6%
,4
44.4%
Space Separator
ValueCountFrequency (%)
75
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin782
90.3%
Common84
 
9.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e88
11.3%
a87
11.1%
o84
10.7%
i68
 
8.7%
r54
 
6.9%
s51
 
6.5%
n45
 
5.8%
d45
 
5.8%
t36
 
4.6%
l32
 
4.1%
Other values (39)192
24.6%
Common
ValueCountFrequency (%)
75
89.3%
/5
 
6.0%
,4
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII846
97.7%
None20
 
2.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e88
10.4%
a87
10.3%
o84
 
9.9%
75
 
8.9%
i68
 
8.0%
r54
 
6.4%
s51
 
6.0%
n45
 
5.3%
d45
 
5.3%
t36
 
4.3%
Other values (35)213
25.2%
None
ValueCountFrequency (%)
ç7
35.0%
ã4
20.0%
á3
15.0%
ú2
 
10.0%
Á2
 
10.0%
ô1
 
5.0%
ó1
 
5.0%

profsex
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)6.0%
Missing7
Missing (%)12.3%
Memory size584.0 B
Não
27 
Sim
21 
Prefiro não responder
 
2

Length

Max length21
Median length3
Mean length3.72
Min length3

Characters and Unicode

Total characters186
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowSim
3rd rowNão
4th rowSim
5th rowSim

Common Values

ValueCountFrequency (%)
Não27
47.4%
Sim21
36.8%
Prefiro não responder2
 
3.5%
(Missing)7
 
12.3%

Length

2022-05-31T15:05:30.764772image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:30.890975image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não29
53.7%
sim21
38.9%
prefiro2
 
3.7%
responder2
 
3.7%

Most occurring characters

ValueCountFrequency (%)
o33
17.7%
ã29
15.6%
N27
14.5%
i23
12.4%
S21
11.3%
m21
11.3%
r8
 
4.3%
e6
 
3.2%
4
 
2.2%
n4
 
2.2%
Other values (5)10
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter132
71.0%
Uppercase Letter50
 
26.9%
Space Separator4
 
2.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o33
25.0%
ã29
22.0%
i23
17.4%
m21
15.9%
r8
 
6.1%
e6
 
4.5%
n4
 
3.0%
f2
 
1.5%
s2
 
1.5%
p2
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
N27
54.0%
S21
42.0%
P2
 
4.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin182
97.8%
Common4
 
2.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
o33
18.1%
ã29
15.9%
N27
14.8%
i23
12.6%
S21
11.5%
m21
11.5%
r8
 
4.4%
e6
 
3.3%
n4
 
2.2%
P2
 
1.1%
Other values (4)8
 
4.4%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII157
84.4%
None29
 
15.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o33
21.0%
N27
17.2%
i23
14.6%
S21
13.4%
m21
13.4%
r8
 
5.1%
e6
 
3.8%
4
 
2.5%
n4
 
2.5%
P2
 
1.3%
Other values (4)8
 
5.1%
None
ValueCountFrequency (%)
ã29
100.0%

renda
Categorical

HIGH CORRELATION
MISSING

Distinct5
Distinct (%)10.2%
Missing8
Missing (%)14.0%
Memory size584.0 B
De 500 a 1.099 reais
14 
De 1.100 a 2.119 reais
13 
Até 99 reais
11 
De 100 a 499 reais
Mais de 2.200 reais (mais de dois salários mínimos)

Length

Max length51
Median length22
Mean length19.63265306
Min length12

Characters and Unicode

Total characters962
Distinct characters27
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAté 99 reais
2nd rowAté 99 reais
3rd rowDe 500 a 1.099 reais
4th rowAté 99 reais
5th rowDe 100 a 499 reais

Common Values

ValueCountFrequency (%)
De 500 a 1.099 reais14
24.6%
De 1.100 a 2.119 reais13
22.8%
Até 99 reais11
19.3%
De 100 a 499 reais9
15.8%
Mais de 2.200 reais (mais de dois salários mínimos)2
 
3.5%
(Missing)8
14.0%

Length

2022-05-31T15:05:31.002677image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:31.139349image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
reais49
21.2%
de40
17.3%
a36
15.6%
50014
 
6.1%
1.09914
 
6.1%
1.10013
 
5.6%
2.11913
 
5.6%
até11
 
4.8%
9911
 
4.8%
1009
 
3.9%
Other values (6)21
9.1%

Most occurring characters

ValueCountFrequency (%)
182
18.9%
a91
9.5%
090
9.4%
e89
9.3%
981
8.4%
175
7.8%
s61
 
6.3%
i59
 
6.1%
r51
 
5.3%
.42
 
4.4%
Other values (17)141
14.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter399
41.5%
Decimal Number286
29.7%
Space Separator182
18.9%
Uppercase Letter49
 
5.1%
Other Punctuation42
 
4.4%
Open Punctuation2
 
0.2%
Close Punctuation2
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a91
22.8%
e89
22.3%
s61
15.3%
i59
14.8%
r51
12.8%
é11
 
2.8%
t11
 
2.8%
d6
 
1.5%
m6
 
1.5%
o6
 
1.5%
Other values (4)8
 
2.0%
Decimal Number
ValueCountFrequency (%)
090
31.5%
981
28.3%
175
26.2%
217
 
5.9%
514
 
4.9%
49
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
D36
73.5%
A11
 
22.4%
M2
 
4.1%
Space Separator
ValueCountFrequency (%)
182
100.0%
Other Punctuation
ValueCountFrequency (%)
.42
100.0%
Open Punctuation
ValueCountFrequency (%)
(2
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common514
53.4%
Latin448
46.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a91
20.3%
e89
19.9%
s61
13.6%
i59
13.2%
r51
11.4%
D36
 
8.0%
é11
 
2.5%
A11
 
2.5%
t11
 
2.5%
d6
 
1.3%
Other values (7)22
 
4.9%
Common
ValueCountFrequency (%)
182
35.4%
090
17.5%
981
15.8%
175
14.6%
.42
 
8.2%
217
 
3.3%
514
 
2.7%
49
 
1.8%
(2
 
0.4%
)2
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII947
98.4%
None15
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
182
19.2%
a91
9.6%
090
9.5%
e89
9.4%
981
8.6%
175
7.9%
s61
 
6.4%
i59
 
6.2%
r51
 
5.4%
.42
 
4.4%
Other values (14)126
13.3%
None
ValueCountFrequency (%)
é11
73.3%
á2
 
13.3%
í2
 
13.3%

depndfam
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)8.0%
Missing7
Missing (%)12.3%
Memory size584.0 B
Sim, em partes
24 
Não
18 
Sim, completamente
oGWAcvnZXq8gVeTvTM/KyGKCyAmW1SWKlHlbGPdyNaM5l+KevFG6NCMtc7rWcxz1LN5WsG4EjTanFiAUudh76QmnV5xK25m/zYYNGC5aJElBw0MBPAvYFphn7648K7Ix6U4JYGicK8wu1yJVVTsA6hJASjRtpUMIqcbpkTQk2t4No9SQ0xTPUYKL7Pe9MtjltrVLM2Ex0G72B7gLR2Vo4GURLjhEugJ8+UJJrH9hofMwLx2u/TViCpNRldxovkLE/aSXEioeIWKMdBqkPnl+6gYyqwxnoLeMyATHfFNKnrV6E14CJwIFDIfmp0Z024Q6hobw/pV3SQ0wfY1kVRGU
 
1

Length

Max length340
Median length18
Mean length17.12
Min length3

Characters and Unicode

Total characters856
Distinct characters66
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)2.0%

Sample

1st rowSim, em partes
2nd rowSim, em partes
3rd rowSim, completamente
4th rowSim, em partes
5th rowSim, em partes

Common Values

ValueCountFrequency (%)
Sim, em partes24
42.1%
Não18
31.6%
Sim, completamente7
 
12.3%
oGWAcvnZXq8gVeTvTM/KyGKCyAmW1SWKlHlbGPdyNaM5l+KevFG6NCMtc7rWcxz1LN5WsG4EjTanFiAUudh76QmnV5xK25m/zYYNGC5aJElBw0MBPAvYFphn7648K7Ix6U4JYGicK8wu1yJVVTsA6hJASjRtpUMIqcbpkTQk2t4No9SQ0xTPUYKL7Pe9MtjltrVLM2Ex0G72B7gLR2Vo4GURLjhEugJ8+UJJrH9hofMwLx2u/TViCpNRldxovkLE/aSXEioeIWKMdBqkPnl+6gYyqwxnoLeMyATHfFNKnrV6E14CJwIFDIfmp0Z024Q6hobw/pV3SQ0wfY1kVRGU1
 
1.8%
(Missing)7
 
12.3%

Length

2022-05-31T15:05:31.293896image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:31.438511image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim31
29.5%
em24
22.9%
partes24
22.9%
não18
17.1%
completamente7
 
6.7%
ogwacvnzxq8gvetvtm/kygkcyamw1swklhlbgpdynam5l+kevfg6ncmtc7rwcxz1ln5wsg4ejtanfiauudh76qmnv5xk25m/zyyngc5ajelbw0mbpavyfphn7648k7ix6u4jygick8wu1yjvvtsa6hjasjrtpumiqcbpktqk2t4no9sq0xtpuykl7pe9mtjltrvlm2ex0g72b7glr2vo4gurljheugj8+ujjrh9hofmwlx2u/tvicpnrldxovkle/asxeioeiwkmdbqkpnl+6gyyqwxnolemyathffnknrv6e14cjwifdifmp0z024q6hobw/pv3sq0wfy1kvrgu1
 
1.0%

Most occurring characters

ValueCountFrequency (%)
e74
 
8.6%
m73
 
8.5%
55
 
6.4%
t43
 
5.0%
p37
 
4.3%
S36
 
4.2%
a35
 
4.1%
i35
 
4.1%
o33
 
3.9%
,31
 
3.6%
Other values (56)404
47.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter508
59.3%
Uppercase Letter201
 
23.5%
Space Separator55
 
6.4%
Decimal Number53
 
6.2%
Other Punctuation36
 
4.2%
Math Symbol3
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e74
14.6%
m73
14.4%
t43
8.5%
p37
 
7.3%
a35
 
6.9%
i35
 
6.9%
o33
 
6.5%
r28
 
5.5%
s26
 
5.1%
ã18
 
3.5%
Other values (17)106
20.9%
Uppercase Letter
ValueCountFrequency (%)
S36
17.9%
N25
 
12.4%
G10
 
5.0%
K10
 
5.0%
M10
 
5.0%
V10
 
5.0%
L8
 
4.0%
J8
 
4.0%
T8
 
4.0%
Y7
 
3.5%
Other values (15)69
34.3%
Decimal Number
ValueCountFrequency (%)
68
15.1%
77
13.2%
27
13.2%
47
13.2%
06
11.3%
15
9.4%
55
9.4%
84
7.5%
93
 
5.7%
31
 
1.9%
Other Punctuation
ValueCountFrequency (%)
,31
86.1%
/5
 
13.9%
Space Separator
ValueCountFrequency (%)
55
100.0%
Math Symbol
ValueCountFrequency (%)
+3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin709
82.8%
Common147
 
17.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e74
 
10.4%
m73
 
10.3%
t43
 
6.1%
p37
 
5.2%
S36
 
5.1%
a35
 
4.9%
i35
 
4.9%
o33
 
4.7%
r28
 
3.9%
s26
 
3.7%
Other values (42)289
40.8%
Common
ValueCountFrequency (%)
55
37.4%
,31
21.1%
68
 
5.4%
77
 
4.8%
27
 
4.8%
47
 
4.8%
06
 
4.1%
15
 
3.4%
/5
 
3.4%
55
 
3.4%
Other values (4)11
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII838
97.9%
None18
 
2.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e74
 
8.8%
m73
 
8.7%
55
 
6.6%
t43
 
5.1%
p37
 
4.4%
S36
 
4.3%
a35
 
4.2%
i35
 
4.2%
o33
 
3.9%
,31
 
3.7%
Other values (55)386
46.1%
None
ValueCountFrequency (%)
ã18
100.0%

usomei
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)4.4%
Missing12
Missing (%)21.1%
Memory size584.0 B
Não
40 
Sim

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters135
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão
2nd rowNão
3rd rowNão
4th rowSim
5th rowNão

Common Values

ValueCountFrequency (%)
Não40
70.2%
Sim5
 
8.8%
(Missing)12
 
21.1%

Length

2022-05-31T15:05:31.633527image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:31.763180image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não40
88.9%
sim5
 
11.1%

Most occurring characters

ValueCountFrequency (%)
N40
29.6%
ã40
29.6%
o40
29.6%
S5
 
3.7%
i5
 
3.7%
m5
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter90
66.7%
Uppercase Letter45
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
ã40
44.4%
o40
44.4%
i5
 
5.6%
m5
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
N40
88.9%
S5
 
11.1%

Most occurring scripts

ValueCountFrequency (%)
Latin135
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N40
29.6%
ã40
29.6%
o40
29.6%
S5
 
3.7%
i5
 
3.7%
m5
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII95
70.4%
None40
29.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N40
42.1%
o40
42.1%
S5
 
5.3%
i5
 
5.3%
m5
 
5.3%
None
ValueCountFrequency (%)
ã40
100.0%

nomesoctrb
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)4.1%
Missing8
Missing (%)14.0%
Memory size584.0 B
Sim
34 
Não
15 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters147
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowSim
3rd rowSim
4th rowSim
5th rowSim

Common Values

ValueCountFrequency (%)
Sim34
59.6%
Não15
26.3%
(Missing)8
 
14.0%

Length

2022-05-31T15:05:31.865909image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:31.983162image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim34
69.4%
não15
30.6%

Most occurring characters

ValueCountFrequency (%)
S34
23.1%
i34
23.1%
m34
23.1%
N15
10.2%
ã15
10.2%
o15
10.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter98
66.7%
Uppercase Letter49
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i34
34.7%
m34
34.7%
ã15
15.3%
o15
15.3%
Uppercase Letter
ValueCountFrequency (%)
S34
69.4%
N15
30.6%

Most occurring scripts

ValueCountFrequency (%)
Latin147
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S34
23.1%
i34
23.1%
m34
23.1%
N15
10.2%
ã15
10.2%
o15
10.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII132
89.8%
None15
 
10.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S34
25.8%
i34
25.8%
m34
25.8%
N15
11.4%
o15
11.4%
None
ValueCountFrequency (%)
ã15
100.0%

pqnaousanm
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)21.4%
Missing43
Missing (%)75.4%
Memory size584.0 B
Isso não é uma questão para mim
11 
Não existe uma política para uso do nome social
Alguns colegas respeitam, outros não
 
1

Length

Max length47
Median length31
Mean length33.64285714
Min length31

Characters and Unicode

Total characters471
Distinct characters25
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)7.1%

Sample

1st rowIsso não é uma questão para mim
2nd rowIsso não é uma questão para mim
3rd rowAlguns colegas respeitam, outros não
4th rowIsso não é uma questão para mim
5th rowIsso não é uma questão para mim

Common Values

ValueCountFrequency (%)
Isso não é uma questão para mim11
 
19.3%
Não existe uma política para uso do nome social2
 
3.5%
Alguns colegas respeitam, outros não1
 
1.8%
(Missing)43
75.4%

Length

2022-05-31T15:05:32.108825image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:32.240512image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não14
14.0%
uma13
13.0%
para13
13.0%
isso11
11.0%
é11
11.0%
questão11
11.0%
mim11
11.0%
do2
 
2.0%
social2
 
2.0%
nome2
 
2.0%
Other values (7)10
10.0%

Most occurring characters

ValueCountFrequency (%)
86
18.3%
o49
10.4%
a45
9.6%
s43
9.1%
m38
 
8.1%
u28
 
5.9%
ã25
 
5.3%
e20
 
4.2%
i18
 
3.8%
t17
 
3.6%
Other values (15)102
21.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter370
78.6%
Space Separator86
 
18.3%
Uppercase Letter14
 
3.0%
Other Punctuation1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o49
13.2%
a45
12.2%
s43
11.6%
m38
10.3%
u28
 
7.6%
ã25
 
6.8%
e20
 
5.4%
i18
 
4.9%
t17
 
4.6%
p16
 
4.3%
Other values (10)71
19.2%
Uppercase Letter
ValueCountFrequency (%)
I11
78.6%
N2
 
14.3%
A1
 
7.1%
Space Separator
ValueCountFrequency (%)
86
100.0%
Other Punctuation
ValueCountFrequency (%)
,1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin384
81.5%
Common87
 
18.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
o49
12.8%
a45
11.7%
s43
11.2%
m38
9.9%
u28
 
7.3%
ã25
 
6.5%
e20
 
5.2%
i18
 
4.7%
t17
 
4.4%
p16
 
4.2%
Other values (13)85
22.1%
Common
ValueCountFrequency (%)
86
98.9%
,1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII433
91.9%
None38
 
8.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
86
19.9%
o49
11.3%
a45
10.4%
s43
9.9%
m38
8.8%
u28
 
6.5%
e20
 
4.6%
i18
 
4.2%
t17
 
3.9%
p16
 
3.7%
Other values (12)73
16.9%
None
ValueCountFrequency (%)
ã25
65.8%
é11
28.9%
í2
 
5.3%

assdtrb
Categorical

HIGH CORRELATION
MISSING

Distinct9
Distinct (%)18.4%
Missing8
Missing (%)14.0%
Memory size584.0 B
Não, nunca sofri nenhum tipo de assédio no trabalho
22 
Sim, assédio moral Sim, assédio sexual Sim, assédio psicológico
11 
Sim, assédio moral Sim, assédio psicológico
Sim, assédio sexual Sim, assédio psicológico
Sim, assédio moral
Other values (4)

Length

Max length95
Median length63
Mean length49.30612245
Min length18

Characters and Unicode

Total characters2416
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)6.1%

Sample

1st rowNão, nunca sofri nenhum tipo de assédio no trabalho
2nd rowNão, nunca sofri nenhum tipo de assédio no trabalho
3rd rowNão, nunca sofri nenhum tipo de assédio no trabalho
4th rowSim, assédio moral Sim, assédio sexual Sim, assédio psicológico
5th rowNão, nunca sofri nenhum tipo de assédio no trabalho

Common Values

ValueCountFrequency (%)
Não, nunca sofri nenhum tipo de assédio no trabalho22
38.6%
Sim, assédio moral Sim, assédio sexual Sim, assédio psicológico11
19.3%
Sim, assédio moral Sim, assédio psicológico5
 
8.8%
Sim, assédio sexual Sim, assédio psicológico3
 
5.3%
Sim, assédio moral3
 
5.3%
Sim, assédio psicológico2
 
3.5%
Sim, assédio sexual1
 
1.8%
Não, nunca sofri nenhum tipo de assédio no trabalho Sim, assédio moral Sim, assédio psicológico1
 
1.8%
Sim, assédio moral Sim, assédio sexual1
 
1.8%
(Missing)8
 
14.0%

Length

2022-05-31T15:05:32.377109image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:32.528702image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
assédio82
21.4%
sim59
15.4%
não23
 
6.0%
nunca23
 
6.0%
sofri23
 
6.0%
nenhum23
 
6.0%
tipo23
 
6.0%
de23
 
6.0%
no23
 
6.0%
trabalho23
 
6.0%
Other values (3)59
15.4%

Most occurring characters

ValueCountFrequency (%)
335
13.9%
o262
 
10.8%
i231
 
9.6%
s225
 
9.3%
a188
 
7.8%
n115
 
4.8%
d105
 
4.3%
m103
 
4.3%
é82
 
3.4%
l82
 
3.4%
Other values (16)688
28.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1917
79.3%
Space Separator335
 
13.9%
Other Punctuation82
 
3.4%
Uppercase Letter82
 
3.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o262
13.7%
i231
12.1%
s225
11.7%
a188
9.8%
n115
 
6.0%
d105
 
5.5%
m103
 
5.4%
é82
 
4.3%
l82
 
4.3%
c67
 
3.5%
Other values (12)457
23.8%
Uppercase Letter
ValueCountFrequency (%)
S59
72.0%
N23
 
28.0%
Space Separator
ValueCountFrequency (%)
335
100.0%
Other Punctuation
ValueCountFrequency (%)
,82
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1999
82.7%
Common417
 
17.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o262
13.1%
i231
11.6%
s225
11.3%
a188
 
9.4%
n115
 
5.8%
d105
 
5.3%
m103
 
5.2%
é82
 
4.1%
l82
 
4.1%
c67
 
3.4%
Other values (14)539
27.0%
Common
ValueCountFrequency (%)
335
80.3%
,82
 
19.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII2289
94.7%
None127
 
5.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
335
14.6%
o262
11.4%
i231
10.1%
s225
9.8%
a188
 
8.2%
n115
 
5.0%
d105
 
4.6%
m103
 
4.5%
l82
 
3.6%
,82
 
3.6%
Other values (13)561
24.5%
None
ValueCountFrequency (%)
é82
64.6%
ã23
 
18.1%
ó22
 
17.3%

discrsectrb
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)8.2%
Missing8
Missing (%)14.0%
Memory size584.0 B
não, nunca sofri
23 
sim, mais de uma vez/ regularmente
18 
sim, uma vez
prefiro não responder
 
1

Length

Max length34
Median length21
Mean length22.14285714
Min length12

Characters and Unicode

Total characters1085
Distinct characters22
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)2.0%

Sample

1st rownão, nunca sofri
2nd rownão, nunca sofri
3rd rownão, nunca sofri
4th rowsim, mais de uma vez/ regularmente
5th rownão, nunca sofri

Common Values

ValueCountFrequency (%)
não, nunca sofri23
40.4%
sim, mais de uma vez/ regularmente18
31.6%
sim, uma vez7
 
12.3%
prefiro não responder1
 
1.8%
(Missing)8
 
14.0%

Length

2022-05-31T15:05:32.719232image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:32.838872image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim25
12.4%
uma25
12.4%
vez25
12.4%
não24
11.9%
nunca23
11.4%
sofri23
11.4%
mais18
9.0%
de18
9.0%
regularmente18
9.0%
prefiro1
 
0.5%

Most occurring characters

ValueCountFrequency (%)
152
14.0%
e100
 
9.2%
n89
 
8.2%
m86
 
7.9%
a84
 
7.7%
s67
 
6.2%
i67
 
6.2%
u66
 
6.1%
r63
 
5.8%
o49
 
4.5%
Other values (12)262
24.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter867
79.9%
Space Separator152
 
14.0%
Other Punctuation66
 
6.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e100
11.5%
n89
10.3%
m86
9.9%
a84
9.7%
s67
 
7.7%
i67
 
7.7%
u66
 
7.6%
r63
 
7.3%
o49
 
5.7%
v25
 
2.9%
Other values (9)171
19.7%
Other Punctuation
ValueCountFrequency (%)
,48
72.7%
/18
 
27.3%
Space Separator
ValueCountFrequency (%)
152
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin867
79.9%
Common218
 
20.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e100
11.5%
n89
10.3%
m86
9.9%
a84
9.7%
s67
 
7.7%
i67
 
7.7%
u66
 
7.6%
r63
 
7.3%
o49
 
5.7%
v25
 
2.9%
Other values (9)171
19.7%
Common
ValueCountFrequency (%)
152
69.7%
,48
 
22.0%
/18
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII1061
97.8%
None24
 
2.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
152
14.3%
e100
9.4%
n89
 
8.4%
m86
 
8.1%
a84
 
7.9%
s67
 
6.3%
i67
 
6.3%
u66
 
6.2%
r63
 
5.9%
o49
 
4.6%
Other values (11)238
22.4%
None
ValueCountFrequency (%)
ã24
100.0%

discractrb
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)6.1%
Missing8
Missing (%)14.0%
Memory size584.0 B
não, nunca sofri
39 
sim, mais de uma vez/ regularmente
sim, uma vez

Length

Max length34
Median length16
Mean length17.87755102
Min length12

Characters and Unicode

Total characters876
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rownão, nunca sofri
2nd rownão, nunca sofri
3rd rownão, nunca sofri
4th rowsim, mais de uma vez/ regularmente
5th rownão, nunca sofri

Common Values

ValueCountFrequency (%)
não, nunca sofri39
68.4%
sim, mais de uma vez/ regularmente6
 
10.5%
sim, uma vez4
 
7.0%
(Missing)8
 
14.0%

Length

2022-05-31T15:05:32.959225image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:33.070924image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não39
23.6%
nunca39
23.6%
sofri39
23.6%
sim10
 
6.1%
uma10
 
6.1%
vez10
 
6.1%
mais6
 
3.6%
de6
 
3.6%
regularmente6
 
3.6%

Most occurring characters

ValueCountFrequency (%)
n123
14.0%
116
13.2%
o78
8.9%
a61
 
7.0%
i55
 
6.3%
u55
 
6.3%
s55
 
6.3%
r51
 
5.8%
,49
 
5.6%
c39
 
4.5%
Other values (11)194
22.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter705
80.5%
Space Separator116
 
13.2%
Other Punctuation55
 
6.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n123
17.4%
o78
11.1%
a61
8.7%
i55
7.8%
u55
7.8%
s55
7.8%
r51
7.2%
c39
 
5.5%
f39
 
5.5%
ã39
 
5.5%
Other values (8)110
15.6%
Other Punctuation
ValueCountFrequency (%)
,49
89.1%
/6
 
10.9%
Space Separator
ValueCountFrequency (%)
116
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin705
80.5%
Common171
 
19.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
n123
17.4%
o78
11.1%
a61
8.7%
i55
7.8%
u55
7.8%
s55
7.8%
r51
7.2%
c39
 
5.5%
f39
 
5.5%
ã39
 
5.5%
Other values (8)110
15.6%
Common
ValueCountFrequency (%)
116
67.8%
,49
28.7%
/6
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII837
95.5%
None39
 
4.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n123
14.7%
116
13.9%
o78
9.3%
a61
 
7.3%
i55
 
6.6%
u55
 
6.6%
s55
 
6.6%
r51
 
6.1%
,49
 
5.9%
c39
 
4.7%
Other values (10)155
18.5%
None
ValueCountFrequency (%)
ã39
100.0%

bolsafam
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)8.0%
Missing7
Missing (%)12.3%
Memory size584.0 B
Sim
22 
Não, porque não me enquadrei nos requisitos
11 
Não solicitei
11 
Não sei como devo fazer para acessar

Length

Max length43
Median length36
Mean length17.96
Min length3

Characters and Unicode

Total characters898
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowNão, porque não me enquadrei nos requisitos
3rd rowNão solicitei
4th rowNão sei como devo fazer para acessar
5th rowSim

Common Values

ValueCountFrequency (%)
Sim22
38.6%
Não, porque não me enquadrei nos requisitos11
19.3%
Não solicitei11
19.3%
Não sei como devo fazer para acessar6
 
10.5%
(Missing)7
 
12.3%

Length

2022-05-31T15:05:33.188611image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:33.334257image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não39
23.9%
sim22
13.5%
porque11
 
6.7%
me11
 
6.7%
enquadrei11
 
6.7%
nos11
 
6.7%
requisitos11
 
6.7%
solicitei11
 
6.7%
sei6
 
3.7%
como6
 
3.7%
Other values (4)24
14.7%

Most occurring characters

ValueCountFrequency (%)
113
12.6%
o101
11.2%
i94
 
10.5%
e90
 
10.0%
s62
 
6.9%
r51
 
5.7%
a41
 
4.6%
m39
 
4.3%
ã39
 
4.3%
u33
 
3.7%
Other values (13)235
26.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter724
80.6%
Space Separator113
 
12.6%
Uppercase Letter50
 
5.6%
Other Punctuation11
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o101
14.0%
i94
13.0%
e90
12.4%
s62
8.6%
r51
 
7.0%
a41
 
5.7%
m39
 
5.4%
ã39
 
5.4%
u33
 
4.6%
q33
 
4.6%
Other values (9)141
19.5%
Uppercase Letter
ValueCountFrequency (%)
N28
56.0%
S22
44.0%
Space Separator
ValueCountFrequency (%)
113
100.0%
Other Punctuation
ValueCountFrequency (%)
,11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin774
86.2%
Common124
 
13.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
o101
13.0%
i94
12.1%
e90
11.6%
s62
 
8.0%
r51
 
6.6%
a41
 
5.3%
m39
 
5.0%
ã39
 
5.0%
u33
 
4.3%
q33
 
4.3%
Other values (11)191
24.7%
Common
ValueCountFrequency (%)
113
91.1%
,11
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII859
95.7%
None39
 
4.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
113
13.2%
o101
11.8%
i94
10.9%
e90
10.5%
s62
 
7.2%
r51
 
5.9%
a41
 
4.8%
m39
 
4.5%
u33
 
3.8%
q33
 
3.8%
Other values (12)202
23.5%
None
ValueCountFrequency (%)
ã39
100.0%

ctbolsafam
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)4.1%
Missing8
Missing (%)14.0%
Memory size584.0 B
Não
36 
Sim
13 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters147
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão
2nd rowNão
3rd rowNão
4th rowSim
5th rowNão

Common Values

ValueCountFrequency (%)
Não36
63.2%
Sim13
 
22.8%
(Missing)8
 
14.0%

Length

2022-05-31T15:05:33.457493image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:33.572186image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não36
73.5%
sim13
 
26.5%

Most occurring characters

ValueCountFrequency (%)
N36
24.5%
ã36
24.5%
o36
24.5%
S13
 
8.8%
i13
 
8.8%
m13
 
8.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter98
66.7%
Uppercase Letter49
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
ã36
36.7%
o36
36.7%
i13
 
13.3%
m13
 
13.3%
Uppercase Letter
ValueCountFrequency (%)
N36
73.5%
S13
 
26.5%

Most occurring scripts

ValueCountFrequency (%)
Latin147
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N36
24.5%
ã36
24.5%
o36
24.5%
S13
 
8.8%
i13
 
8.8%
m13
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII111
75.5%
None36
 
24.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N36
32.4%
o36
32.4%
S13
 
11.7%
i13
 
11.7%
m13
 
11.7%
None
ValueCountFrequency (%)
ã36
100.0%

demisidgen
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)6.1%
Missing8
Missing (%)14.0%
Memory size584.0 B
não
33 
sim
11 
não sei

Length

Max length7
Median length3
Mean length3.408163265
Min length3

Characters and Unicode

Total characters167
Distinct characters8
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rownão sei
2nd rownão
3rd rownão
4th rowsim
5th rownão

Common Values

ValueCountFrequency (%)
não33
57.9%
sim11
 
19.3%
não sei5
 
8.8%
(Missing)8
 
14.0%

Length

2022-05-31T15:05:33.673912image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:33.797583image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não38
70.4%
sim11
 
20.4%
sei5
 
9.3%

Most occurring characters

ValueCountFrequency (%)
n38
22.8%
ã38
22.8%
o38
22.8%
s16
9.6%
i16
9.6%
m11
 
6.6%
5
 
3.0%
e5
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter162
97.0%
Space Separator5
 
3.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n38
23.5%
ã38
23.5%
o38
23.5%
s16
9.9%
i16
9.9%
m11
 
6.8%
e5
 
3.1%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin162
97.0%
Common5
 
3.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n38
23.5%
ã38
23.5%
o38
23.5%
s16
9.9%
i16
9.9%
m11
 
6.8%
e5
 
3.1%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII129
77.2%
None38
 
22.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n38
29.5%
o38
29.5%
s16
12.4%
i16
12.4%
m11
 
8.5%
5
 
3.9%
e5
 
3.9%
None
ValueCountFrequency (%)
ã38
100.0%

dempand
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)4.3%
Missing10
Missing (%)17.5%
Memory size584.0 B
Não
40 
Sim

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters141
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão
2nd rowNão
3rd rowNão
4th rowNão
5th rowNão

Common Values

ValueCountFrequency (%)
Não40
70.2%
Sim7
 
12.3%
(Missing)10
 
17.5%

Length

2022-05-31T15:05:33.899348image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:34.004029image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não40
85.1%
sim7
 
14.9%

Most occurring characters

ValueCountFrequency (%)
N40
28.4%
ã40
28.4%
o40
28.4%
S7
 
5.0%
i7
 
5.0%
m7
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter94
66.7%
Uppercase Letter47
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
ã40
42.6%
o40
42.6%
i7
 
7.4%
m7
 
7.4%
Uppercase Letter
ValueCountFrequency (%)
N40
85.1%
S7
 
14.9%

Most occurring scripts

ValueCountFrequency (%)
Latin141
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N40
28.4%
ã40
28.4%
o40
28.4%
S7
 
5.0%
i7
 
5.0%
m7
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII101
71.6%
None40
 
28.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N40
39.6%
o40
39.6%
S7
 
6.9%
i7
 
6.9%
m7
 
6.9%
None
ValueCountFrequency (%)
ã40
100.0%

auxemerg
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)8.0%
Missing7
Missing (%)12.3%
Memory size584.0 B
Sim
31 
Não, porque não me enquadrei nos requisitos
10 
Não, porque fui recusada
Não solicitei
 
2

Length

Max length43
Median length3
Mean length14.34
Min length3

Characters and Unicode

Total characters717
Distinct characters21
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão, porque fui recusada
2nd rowSim
3rd rowNão, porque fui recusada
4th rowSim
5th rowSim

Common Values

ValueCountFrequency (%)
Sim31
54.4%
Não, porque não me enquadrei nos requisitos10
 
17.5%
Não, porque fui recusada7
 
12.3%
Não solicitei2
 
3.5%
(Missing)7
 
12.3%

Length

2022-05-31T15:05:34.112639image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:34.246281image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim31
23.3%
não29
21.8%
porque17
12.8%
me10
 
7.5%
enquadrei10
 
7.5%
nos10
 
7.5%
requisitos10
 
7.5%
fui7
 
5.3%
recusada7
 
5.3%
solicitei2
 
1.5%

Most occurring characters

ValueCountFrequency (%)
83
11.6%
i74
10.3%
o68
 
9.5%
e66
 
9.2%
u51
 
7.1%
r44
 
6.1%
m41
 
5.7%
s39
 
5.4%
q37
 
5.2%
S31
 
4.3%
Other values (11)183
25.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter567
79.1%
Space Separator83
 
11.6%
Uppercase Letter50
 
7.0%
Other Punctuation17
 
2.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i74
13.1%
o68
12.0%
e66
11.6%
u51
9.0%
r44
7.8%
m41
7.2%
s39
6.9%
q37
6.5%
n30
 
5.3%
ã29
 
5.1%
Other values (7)88
15.5%
Uppercase Letter
ValueCountFrequency (%)
S31
62.0%
N19
38.0%
Space Separator
ValueCountFrequency (%)
83
100.0%
Other Punctuation
ValueCountFrequency (%)
,17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin617
86.1%
Common100
 
13.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
i74
12.0%
o68
11.0%
e66
10.7%
u51
 
8.3%
r44
 
7.1%
m41
 
6.6%
s39
 
6.3%
q37
 
6.0%
S31
 
5.0%
n30
 
4.9%
Other values (9)136
22.0%
Common
ValueCountFrequency (%)
83
83.0%
,17
 
17.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII688
96.0%
None29
 
4.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
83
12.1%
i74
10.8%
o68
9.9%
e66
9.6%
u51
 
7.4%
r44
 
6.4%
m41
 
6.0%
s39
 
5.7%
q37
 
5.4%
S31
 
4.5%
Other values (10)154
22.4%
None
ValueCountFrequency (%)
ã29
100.0%

estud
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)7.4%
Missing3
Missing (%)5.3%
Memory size584.0 B
Não, parei/desisti por outros motivos
17 
Não, já concluí meus estudos
17 
Sim
15 
Não, parei/desisti por vontade própria

Length

Max length38
Median length37
Mean length24.81481481
Min length3

Characters and Unicode

Total characters1340
Distinct characters25
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão, parei/desisti por outros motivos
2nd rowNão, parei/desisti por outros motivos
3rd rowNão, já concluí meus estudos
4th rowSim
5th rowNão, já concluí meus estudos

Common Values

ValueCountFrequency (%)
Não, parei/desisti por outros motivos17
29.8%
Não, já concluí meus estudos17
29.8%
Sim15
26.3%
Não, parei/desisti por vontade própria5
 
8.8%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:34.374977image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:34.498605image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não39
18.6%
parei/desisti22
10.5%
por22
10.5%
outros17
8.1%
motivos17
8.1%
17
8.1%
concluí17
8.1%
meus17
8.1%
estudos17
8.1%
sim15
 
7.1%
Other values (2)10
 
4.8%

Most occurring characters

ValueCountFrequency (%)
o168
12.5%
156
11.6%
s129
 
9.6%
i103
 
7.7%
e83
 
6.2%
t78
 
5.8%
r71
 
5.3%
u68
 
5.1%
p54
 
4.0%
m49
 
3.7%
Other values (15)381
28.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1069
79.8%
Space Separator156
 
11.6%
Other Punctuation61
 
4.6%
Uppercase Letter54
 
4.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o168
15.7%
s129
12.1%
i103
9.6%
e83
 
7.8%
t78
 
7.3%
r71
 
6.6%
u68
 
6.4%
p54
 
5.1%
m49
 
4.6%
d44
 
4.1%
Other values (10)222
20.8%
Uppercase Letter
ValueCountFrequency (%)
N39
72.2%
S15
 
27.8%
Other Punctuation
ValueCountFrequency (%)
,39
63.9%
/22
36.1%
Space Separator
ValueCountFrequency (%)
156
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1123
83.8%
Common217
 
16.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
o168
15.0%
s129
11.5%
i103
 
9.2%
e83
 
7.4%
t78
 
6.9%
r71
 
6.3%
u68
 
6.1%
p54
 
4.8%
m49
 
4.4%
d44
 
3.9%
Other values (12)276
24.6%
Common
ValueCountFrequency (%)
156
71.9%
,39
 
18.0%
/22
 
10.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII1262
94.2%
None78
 
5.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o168
13.3%
156
12.4%
s129
10.2%
i103
 
8.2%
e83
 
6.6%
t78
 
6.2%
r71
 
5.6%
u68
 
5.4%
p54
 
4.3%
m49
 
3.9%
Other values (11)303
24.0%
None
ValueCountFrequency (%)
ã39
50.0%
á17
21.8%
í17
21.8%
ó5
 
6.4%

tpinstitu
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)3.7%
Missing3
Missing (%)5.3%
Memory size584.0 B
Pública
47 
Privada

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters378
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPública
2nd rowPública
3rd rowPública
4th rowPública
5th rowPública

Common Values

ValueCountFrequency (%)
Pública47
82.5%
Privada7
 
12.3%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:34.618326image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:34.725999image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
pública47
87.0%
privada7
 
13.0%

Most occurring characters

ValueCountFrequency (%)
a61
16.1%
P54
14.3%
i54
14.3%
ú47
12.4%
b47
12.4%
l47
12.4%
c47
12.4%
r7
 
1.9%
v7
 
1.9%
d7
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter324
85.7%
Uppercase Letter54
 
14.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a61
18.8%
i54
16.7%
ú47
14.5%
b47
14.5%
l47
14.5%
c47
14.5%
r7
 
2.2%
v7
 
2.2%
d7
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
P54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin378
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a61
16.1%
P54
14.3%
i54
14.3%
ú47
12.4%
b47
12.4%
l47
12.4%
c47
12.4%
r7
 
1.9%
v7
 
1.9%
d7
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII331
87.6%
None47
 
12.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a61
18.4%
P54
16.3%
i54
16.3%
b47
14.2%
l47
14.2%
c47
14.2%
r7
 
2.1%
v7
 
2.1%
d7
 
2.1%
None
ValueCountFrequency (%)
ú47
100.0%

matergrts
Categorical

HIGH CORRELATION
MISSING

Distinct7
Distinct (%)13.0%
Missing3
Missing (%)5.3%
Memory size584.0 B
Sim, oferece livros didáticos Sim, oferece cadernos, lápis, canetas… Sim, oferece uniforme
17 
Não oferece materiais gratuitos
14 
Sim, oferece livros didáticos
10 
Sim, oferece cadernos, lápis, canetas…
Sim, oferece livros didáticos Sim, oferece cadernos, lápis, canetas…
Other values (2)

Length

Max length90
Median length68
Mean length54.55555556
Min length29

Characters and Unicode

Total characters2946
Distinct characters24
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st rowNão oferece materiais gratuitos
2nd rowSim, oferece livros didáticos Sim, oferece cadernos, lápis, canetas… Sim, oferece uniforme
3rd rowSim, oferece livros didáticos Sim, oferece cadernos, lápis, canetas… Sim, oferece uniforme
4th rowSim, oferece livros didáticos Sim, oferece cadernos, lápis, canetas… Sim, oferece uniforme
5th rowSim, oferece cadernos, lápis, canetas…

Common Values

ValueCountFrequency (%)
Sim, oferece livros didáticos Sim, oferece cadernos, lápis, canetas… Sim, oferece uniforme17
29.8%
Não oferece materiais gratuitos14
24.6%
Sim, oferece livros didáticos10
17.5%
Sim, oferece cadernos, lápis, canetas…5
 
8.8%
Sim, oferece livros didáticos Sim, oferece cadernos, lápis, canetas…5
 
8.8%
Sim, oferece livros didáticos Sim, oferece uniforme2
 
3.5%
Sim, oferece cadernos, lápis, canetas… Sim, oferece uniforme1
 
1.8%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:34.828722image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:34.982800image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
oferece96
24.5%
sim82
20.9%
livros34
 
8.7%
didáticos34
 
8.7%
cadernos28
 
7.1%
lápis28
 
7.1%
canetas…28
 
7.1%
uniforme20
 
5.1%
não14
 
3.6%
materiais14
 
3.6%

Most occurring characters

ValueCountFrequency (%)
e378
12.8%
338
11.5%
i274
 
9.3%
o240
 
8.1%
r206
 
7.0%
c186
 
6.3%
s180
 
6.1%
,138
 
4.7%
a126
 
4.3%
m116
 
3.9%
Other values (14)764
25.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2346
79.6%
Space Separator338
 
11.5%
Other Punctuation166
 
5.6%
Uppercase Letter96
 
3.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e378
16.1%
i274
11.7%
o240
10.2%
r206
8.8%
c186
7.9%
s180
7.7%
a126
 
5.4%
m116
 
4.9%
f116
 
4.9%
t104
 
4.4%
Other values (9)420
17.9%
Other Punctuation
ValueCountFrequency (%)
,138
83.1%
28
 
16.9%
Uppercase Letter
ValueCountFrequency (%)
S82
85.4%
N14
 
14.6%
Space Separator
ValueCountFrequency (%)
338
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2442
82.9%
Common504
 
17.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e378
15.5%
i274
11.2%
o240
9.8%
r206
 
8.4%
c186
 
7.6%
s180
 
7.4%
a126
 
5.2%
m116
 
4.8%
f116
 
4.8%
t104
 
4.3%
Other values (11)516
21.1%
Common
ValueCountFrequency (%)
338
67.1%
,138
27.4%
28
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII2842
96.5%
None76
 
2.6%
Punctuation28
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e378
13.3%
338
11.9%
i274
9.6%
o240
 
8.4%
r206
 
7.2%
c186
 
6.5%
s180
 
6.3%
,138
 
4.9%
a126
 
4.4%
m116
 
4.1%
Other values (11)660
23.2%
None
ValueCountFrequency (%)
á62
81.6%
ã14
 
18.4%
Punctuation
ValueCountFrequency (%)
28
100.0%

instiloc
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)5.6%
Missing3
Missing (%)5.3%
Memory size584.0 B
Perto, na mesma comunidade em que vivo
26 
Fora da comunidade onde vivo
25 
Na mesma comunidade em que vivo, porém distante

Length

Max length47
Median length38
Mean length33.87037037
Min length28

Characters and Unicode

Total characters1829
Distinct characters21
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNa mesma comunidade em que vivo, porém distante
2nd rowPerto, na mesma comunidade em que vivo
3rd rowFora da comunidade onde vivo
4th rowFora da comunidade onde vivo
5th rowPerto, na mesma comunidade em que vivo

Common Values

ValueCountFrequency (%)
Perto, na mesma comunidade em que vivo26
45.6%
Fora da comunidade onde vivo25
43.9%
Na mesma comunidade em que vivo, porém distante3
 
5.3%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:35.170295image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:35.306890image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
comunidade54
16.3%
vivo54
16.3%
na29
8.8%
mesma29
8.8%
em29
8.8%
que29
8.8%
perto26
7.9%
fora25
7.6%
da25
7.6%
onde25
7.6%
Other values (2)6
 
1.8%

Most occurring characters

ValueCountFrequency (%)
277
15.1%
e195
10.7%
o187
10.2%
a165
9.0%
d161
8.8%
m144
7.9%
i111
 
6.1%
v108
 
5.9%
n108
 
5.9%
u83
 
4.5%
Other values (11)290
15.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1469
80.3%
Space Separator277
 
15.1%
Uppercase Letter54
 
3.0%
Other Punctuation29
 
1.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e195
13.3%
o187
12.7%
a165
11.2%
d161
11.0%
m144
9.8%
i111
7.6%
v108
7.4%
n108
7.4%
u83
5.7%
r54
 
3.7%
Other values (6)153
10.4%
Uppercase Letter
ValueCountFrequency (%)
P26
48.1%
F25
46.3%
N3
 
5.6%
Space Separator
ValueCountFrequency (%)
277
100.0%
Other Punctuation
ValueCountFrequency (%)
,29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1523
83.3%
Common306
 
16.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e195
12.8%
o187
12.3%
a165
10.8%
d161
10.6%
m144
9.5%
i111
7.3%
v108
7.1%
n108
7.1%
u83
5.4%
r54
 
3.5%
Other values (9)207
13.6%
Common
ValueCountFrequency (%)
277
90.5%
,29
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII1826
99.8%
None3
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
277
15.2%
e195
10.7%
o187
10.2%
a165
9.0%
d161
8.8%
m144
7.9%
i111
 
6.1%
v108
 
5.9%
n108
 
5.9%
u83
 
4.5%
Other values (10)287
15.7%
None
ValueCountFrequency (%)
é3
100.0%

mobinsti
Categorical

HIGH CORRELATION
MISSING

Distinct6
Distinct (%)42.9%
Missing43
Missing (%)75.4%
Memory size584.0 B
Ônibus
Ônibus A pé
Ônibus Metrô
A pé
Ônibus A pé Durante a pandemia é a distancia

Length

Max length44
Median length17
Mean length10.78571429
Min length4

Characters and Unicode

Total characters151
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)14.3%

Sample

1st rowÔnibus
2nd rowÔnibus A pé
3rd rowÔnibus
4th rowÔnibus Metrô
5th rowÔnibus A pé

Common Values

ValueCountFrequency (%)
Ônibus6
 
10.5%
Ônibus A pé2
 
3.5%
Ônibus Metrô2
 
3.5%
A pé2
 
3.5%
Ônibus A pé Durante a pandemia é a distancia1
 
1.8%
Ônibus Metrô A pé1
 
1.8%
(Missing)43
75.4%

Length

2022-05-31T15:05:35.440367image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:35.585975image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
ônibus12
36.4%
a8
24.2%
6
18.2%
metrô3
 
9.1%
durante1
 
3.0%
pandemia1
 
3.0%
é1
 
3.0%
distancia1
 
3.0%

Most occurring characters

ValueCountFrequency (%)
19
12.6%
i15
9.9%
n15
9.9%
u13
8.6%
s13
8.6%
Ô12
 
7.9%
b12
 
7.9%
a7
 
4.6%
p7
 
4.6%
é7
 
4.6%
Other values (10)31
20.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter110
72.8%
Uppercase Letter22
 
14.6%
Space Separator19
 
12.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i15
13.6%
n15
13.6%
u13
11.8%
s13
11.8%
b12
10.9%
a7
6.4%
p7
6.4%
é7
6.4%
e5
 
4.5%
t5
 
4.5%
Other values (5)11
10.0%
Uppercase Letter
ValueCountFrequency (%)
Ô12
54.5%
A6
27.3%
M3
 
13.6%
D1
 
4.5%
Space Separator
ValueCountFrequency (%)
19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin132
87.4%
Common19
 
12.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
i15
11.4%
n15
11.4%
u13
9.8%
s13
9.8%
Ô12
9.1%
b12
9.1%
a7
 
5.3%
p7
 
5.3%
é7
 
5.3%
A6
 
4.5%
Other values (9)25
18.9%
Common
ValueCountFrequency (%)
19
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII129
85.4%
None22
 
14.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19
14.7%
i15
11.6%
n15
11.6%
u13
10.1%
s13
10.1%
b12
9.3%
a7
 
5.4%
p7
 
5.4%
A6
 
4.7%
e5
 
3.9%
Other values (7)17
13.2%
None
ValueCountFrequency (%)
Ô12
54.5%
é7
31.8%
ô3
 
13.6%

pandestd
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)28.6%
Missing43
Missing (%)75.4%
Memory size584.0 B
Tive mais tempo para me dedicar aos estudos
Não consegui me adaptar ao novo modelo de ensino
A escola/universidade não ofereceu aulas remotas
Não tive acesso a materiais e/ou internet

Length

Max length48
Median length45.5
Mean length45.21428571
Min length41

Characters and Unicode

Total characters633
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowA escola/universidade não ofereceu aulas remotas
2nd rowTive mais tempo para me dedicar aos estudos
3rd rowA escola/universidade não ofereceu aulas remotas
4th rowNão consegui me adaptar ao novo modelo de ensino
5th rowNão tive acesso a materiais e/ou internet

Common Values

ValueCountFrequency (%)
Tive mais tempo para me dedicar aos estudos5
 
8.8%
Não consegui me adaptar ao novo modelo de ensino4
 
7.0%
A escola/universidade não ofereceu aulas remotas3
 
5.3%
Não tive acesso a materiais e/ou internet2
 
3.5%
(Missing)43
75.4%

Length

2022-05-31T15:05:35.723607image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:35.855255image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
me9
 
8.3%
não9
 
8.3%
tive7
 
6.5%
tempo5
 
4.6%
para5
 
4.6%
dedicar5
 
4.6%
aos5
 
4.6%
estudos5
 
4.6%
a5
 
4.6%
mais5
 
4.6%
Other values (15)48
44.4%

Most occurring characters

ValueCountFrequency (%)
94
14.8%
e78
12.3%
o65
10.3%
a64
10.1%
s46
 
7.3%
i37
 
5.8%
d33
 
5.2%
m28
 
4.4%
r27
 
4.3%
n26
 
4.1%
Other values (13)135
21.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter520
82.1%
Space Separator94
 
14.8%
Uppercase Letter14
 
2.2%
Other Punctuation5
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e78
15.0%
o65
12.5%
a64
12.3%
s46
8.8%
i37
7.1%
d33
 
6.3%
m28
 
5.4%
r27
 
5.2%
n26
 
5.0%
t25
 
4.8%
Other values (8)91
17.5%
Uppercase Letter
ValueCountFrequency (%)
N6
42.9%
T5
35.7%
A3
21.4%
Space Separator
ValueCountFrequency (%)
94
100.0%
Other Punctuation
ValueCountFrequency (%)
/5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin534
84.4%
Common99
 
15.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e78
14.6%
o65
12.2%
a64
12.0%
s46
8.6%
i37
 
6.9%
d33
 
6.2%
m28
 
5.2%
r27
 
5.1%
n26
 
4.9%
t25
 
4.7%
Other values (11)105
19.7%
Common
ValueCountFrequency (%)
94
94.9%
/5
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII624
98.6%
None9
 
1.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
94
15.1%
e78
12.5%
o65
10.4%
a64
10.3%
s46
 
7.4%
i37
 
5.9%
d33
 
5.3%
m28
 
4.5%
r27
 
4.3%
n26
 
4.2%
Other values (12)126
20.2%
None
ValueCountFrequency (%)
ã9
100.0%

desisest
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)23.5%
Missing40
Missing (%)70.2%
Memory size584.0 B
Falta de tempo para estudar (tive que desistir de estudar para trabalhar, ou cuidar de alguém)
Violências sofridos no âmbito escolar
Expulsão da escola
Não tinha recursos financeiros para estudar (passagens, alimentação, etc.)

Length

Max length94
Median length74
Mean length65.94117647
Min length18

Characters and Unicode

Total characters1121
Distinct characters35
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowExpulsão da escola
2nd rowExpulsão da escola
3rd rowViolências sofridos no âmbito escolar
4th rowViolências sofridos no âmbito escolar
5th rowNão tinha recursos financeiros para estudar (passagens, alimentação, etc.)

Common Values

ValueCountFrequency (%)
Falta de tempo para estudar (tive que desistir de estudar para trabalhar, ou cuidar de alguém)8
 
14.0%
Violências sofridos no âmbito escolar5
 
8.8%
Expulsão da escola2
 
3.5%
Não tinha recursos financeiros para estudar (passagens, alimentação, etc.)2
 
3.5%
(Missing)40
70.2%

Length

2022-05-31T15:05:36.009842image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:36.153457image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
de24
 
13.6%
para18
 
10.2%
estudar18
 
10.2%
falta8
 
4.5%
tempo8
 
4.5%
tive8
 
4.5%
que8
 
4.5%
desistir8
 
4.5%
trabalhar8
 
4.5%
ou8
 
4.5%
Other values (17)61
34.5%

Most occurring characters

ValueCountFrequency (%)
160
14.3%
a136
12.1%
e91
 
8.1%
r84
 
7.5%
s70
 
6.2%
t69
 
6.2%
d65
 
5.8%
i60
 
5.4%
o58
 
5.2%
u54
 
4.8%
Other values (25)274
24.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter910
81.2%
Space Separator160
 
14.3%
Uppercase Letter17
 
1.5%
Other Punctuation14
 
1.2%
Close Punctuation10
 
0.9%
Open Punctuation10
 
0.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a136
14.9%
e91
10.0%
r84
9.2%
s70
 
7.7%
t69
 
7.6%
d65
 
7.1%
i60
 
6.6%
o58
 
6.4%
u54
 
5.9%
l40
 
4.4%
Other values (16)183
20.1%
Uppercase Letter
ValueCountFrequency (%)
F8
47.1%
V5
29.4%
E2
 
11.8%
N2
 
11.8%
Other Punctuation
ValueCountFrequency (%)
,12
85.7%
.2
 
14.3%
Space Separator
ValueCountFrequency (%)
160
100.0%
Close Punctuation
ValueCountFrequency (%)
)10
100.0%
Open Punctuation
ValueCountFrequency (%)
(10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin927
82.7%
Common194
 
17.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a136
14.7%
e91
9.8%
r84
9.1%
s70
 
7.6%
t69
 
7.4%
d65
 
7.0%
i60
 
6.5%
o58
 
6.3%
u54
 
5.8%
l40
 
4.3%
Other values (20)200
21.6%
Common
ValueCountFrequency (%)
160
82.5%
,12
 
6.2%
)10
 
5.2%
(10
 
5.2%
.2
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1095
97.7%
None26
 
2.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
160
14.6%
a136
12.4%
e91
 
8.3%
r84
 
7.7%
s70
 
6.4%
t69
 
6.3%
d65
 
5.9%
i60
 
5.5%
o58
 
5.3%
u54
 
4.9%
Other values (20)248
22.6%
None
ValueCountFrequency (%)
é8
30.8%
ã6
23.1%
ê5
19.2%
â5
19.2%
ç2
 
7.7%

discrescol
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)3.7%
Missing3
Missing (%)5.3%
Memory size584.0 B
Sim
37 
Não
17 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters162
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowNão
3rd rowSim
4th rowNão
5th rowNão

Common Values

ValueCountFrequency (%)
Sim37
64.9%
Não17
29.8%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:36.324002image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:36.455650image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim37
68.5%
não17
31.5%

Most occurring characters

ValueCountFrequency (%)
S37
22.8%
i37
22.8%
m37
22.8%
N17
10.5%
ã17
10.5%
o17
10.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter108
66.7%
Uppercase Letter54
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i37
34.3%
m37
34.3%
ã17
15.7%
o17
15.7%
Uppercase Letter
ValueCountFrequency (%)
S37
68.5%
N17
31.5%

Most occurring scripts

ValueCountFrequency (%)
Latin162
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S37
22.8%
i37
22.8%
m37
22.8%
N17
10.5%
ã17
10.5%
o17
10.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII145
89.5%
None17
 
10.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S37
25.5%
i37
25.5%
m37
25.5%
N17
11.7%
o17
11.7%
None
ValueCountFrequency (%)
ã17
100.0%

tpdiscr
Categorical

HIGH CORRELATION
MISSING

Distinct17
Distinct (%)45.9%
Missing20
Missing (%)35.1%
Memory size584.0 B
Violência de gênero/identidade de gênero Pela minha orientação sexual
Pela minha orientação sexual
Violência de gênero/identidade de gênero
Violência de gênero/identidade de gênero Racismo
Violência de gênero/identidade de gênero Racismo Pela minha orientação sexual Pelo meu comportamento (psicofobia, transtornos, etc.)
Other values (12)
14 

Length

Max length159
Median length124
Mean length66.43243243
Min length7

Characters and Unicode

Total characters2458
Distinct characters32
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)27.0%

Sample

1st rowRacismo
2nd rowPela minha orientação sexual
3rd rowViolência de gênero/identidade de gênero Pela minha orientação sexual
4th rowPor conta do nome
5th rowViolência de gênero/identidade de gênero Pela minha orientação sexual

Common Values

ValueCountFrequency (%)
Violência de gênero/identidade de gênero Pela minha orientação sexual7
 
12.3%
Pela minha orientação sexual6
 
10.5%
Violência de gênero/identidade de gênero4
 
7.0%
Violência de gênero/identidade de gênero Racismo3
 
5.3%
Violência de gênero/identidade de gênero Racismo Pela minha orientação sexual Pelo meu comportamento (psicofobia, transtornos, etc.)3
 
5.3%
Racismo2
 
3.5%
Violência de gênero/identidade de gênero Racismo Pela minha orientação sexual2
 
3.5%
Violência de gênero/identidade de gênero Racismo Pela minha orientação sexual Pelo meu peso (gordofobia) Pelo meu comportamento (psicofobia, transtornos, etc.)1
 
1.8%
Violência de gênero/identidade de gênero Racismo Por ter uma deficiência física e/ou intelectual1
 
1.8%
Pela minha orientação sexual Pelo meu peso (gordofobia)1
 
1.8%
Other values (7)7
 
12.3%
(Missing)20
35.1%

Length

2022-05-31T15:05:36.580355image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
de48
15.2%
violência24
 
7.6%
gênero/identidade24
 
7.6%
gênero24
 
7.6%
pela24
 
7.6%
minha24
 
7.6%
orientação24
 
7.6%
sexual24
 
7.6%
racismo13
 
4.1%
pelo11
 
3.5%
Other values (17)76
24.1%

Most occurring characters

ValueCountFrequency (%)
279
11.4%
e274
11.1%
o225
 
9.2%
a199
 
8.1%
i192
 
7.8%
n179
 
7.3%
d126
 
5.1%
r108
 
4.4%
t103
 
4.2%
l89
 
3.6%
Other values (22)684
27.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2027
82.5%
Space Separator279
 
11.4%
Uppercase Letter76
 
3.1%
Other Punctuation54
 
2.2%
Open Punctuation11
 
0.4%
Close Punctuation11
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e274
13.5%
o225
11.1%
a199
9.8%
i192
9.5%
n179
 
8.8%
d126
 
6.2%
r108
 
5.3%
t103
 
5.1%
l89
 
4.4%
c77
 
3.8%
Other values (13)455
22.4%
Uppercase Letter
ValueCountFrequency (%)
P39
51.3%
V24
31.6%
R13
 
17.1%
Other Punctuation
ValueCountFrequency (%)
/27
50.0%
,18
33.3%
.9
 
16.7%
Space Separator
ValueCountFrequency (%)
279
100.0%
Open Punctuation
ValueCountFrequency (%)
(11
100.0%
Close Punctuation
ValueCountFrequency (%)
)11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2103
85.6%
Common355
 
14.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e274
13.0%
o225
10.7%
a199
 
9.5%
i192
 
9.1%
n179
 
8.5%
d126
 
6.0%
r108
 
5.1%
t103
 
4.9%
l89
 
4.2%
c77
 
3.7%
Other values (16)531
25.2%
Common
ValueCountFrequency (%)
279
78.6%
/27
 
7.6%
,18
 
5.1%
(11
 
3.1%
)11
 
3.1%
.9
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII2332
94.9%
None126
 
5.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
279
12.0%
e274
11.7%
o225
9.6%
a199
 
8.5%
i192
 
8.2%
n179
 
7.7%
d126
 
5.4%
r108
 
4.6%
t103
 
4.4%
l89
 
3.8%
Other values (18)558
23.9%
None
ValueCountFrequency (%)
ê75
59.5%
ã24
 
19.0%
ç24
 
19.0%
í3
 
2.4%

violescol
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)7.4%
Missing3
Missing (%)5.3%
Memory size584.0 B
Nunca sofri/sofro
30 
Sim, sofri/sofro várias vezes
Sim, sofri/sofro poucas vezes
Sim, sofri/sofro algumas vezes

Length

Max length30
Median length17
Mean length22.46296296
Min length17

Characters and Unicode

Total characters1213
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim, sofri/sofro algumas vezes
2nd rowNunca sofri/sofro
3rd rowSim, sofri/sofro poucas vezes
4th rowNunca sofri/sofro
5th rowNunca sofri/sofro

Common Values

ValueCountFrequency (%)
Nunca sofri/sofro30
52.6%
Sim, sofri/sofro várias vezes9
 
15.8%
Sim, sofri/sofro poucas vezes8
 
14.0%
Sim, sofri/sofro algumas vezes7
 
12.3%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:36.713960image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:36.844483image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sofri/sofro54
34.6%
nunca30
19.2%
sim24
15.4%
vezes24
15.4%
várias9
 
5.8%
poucas8
 
5.1%
algumas7
 
4.5%

Most occurring characters

ValueCountFrequency (%)
o170
14.0%
s156
12.9%
r117
9.6%
f108
 
8.9%
i87
 
7.2%
85
 
7.0%
a61
 
5.0%
/54
 
4.5%
e48
 
4.0%
u45
 
3.7%
Other values (13)282
23.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter979
80.7%
Space Separator102
 
8.4%
Other Punctuation78
 
6.4%
Uppercase Letter54
 
4.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o170
17.4%
s156
15.9%
r117
12.0%
f108
11.0%
i87
8.9%
a61
 
6.2%
e48
 
4.9%
u45
 
4.6%
c38
 
3.9%
v33
 
3.4%
Other values (7)116
11.8%
Space Separator
ValueCountFrequency (%)
85
83.3%
 17
 
16.7%
Other Punctuation
ValueCountFrequency (%)
/54
69.2%
,24
30.8%
Uppercase Letter
ValueCountFrequency (%)
N30
55.6%
S24
44.4%

Most occurring scripts

ValueCountFrequency (%)
Latin1033
85.2%
Common180
 
14.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
o170
16.5%
s156
15.1%
r117
11.3%
f108
10.5%
i87
8.4%
a61
 
5.9%
e48
 
4.6%
u45
 
4.4%
c38
 
3.7%
v33
 
3.2%
Other values (9)170
16.5%
Common
ValueCountFrequency (%)
85
47.2%
/54
30.0%
,24
 
13.3%
 17
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII1187
97.9%
None26
 
2.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o170
14.3%
s156
13.1%
r117
9.9%
f108
9.1%
i87
 
7.3%
85
 
7.2%
a61
 
5.1%
/54
 
4.5%
e48
 
4.0%
u45
 
3.8%
Other values (11)256
21.6%
None
ValueCountFrequency (%)
 17
65.4%
á9
34.6%

quemviolescol
Categorical

HIGH CORRELATION
MISSING

Distinct6
Distinct (%)13.6%
Missing13
Missing (%)22.8%
Memory size584.0 B
Por parte dos alunos
19 
Não consigo definir
17 
Por parte dos alunos Por parte dos professores Por parte do corpo administrativo
Por parte dos alunos Por parte dos professores
Por parte do corpo administrativo
 
1

Length

Max length80
Median length46
Mean length26.65909091
Min length19

Characters and Unicode

Total characters1173
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)4.5%

Sample

1st rowPor parte dos alunos
2nd rowNão consigo definir
3rd rowPor parte dos alunos
4th rowNão consigo definir
5th rowPor parte dos alunos

Common Values

ValueCountFrequency (%)
Por parte dos alunos19
33.3%
Não consigo definir17
29.8%
Por parte dos alunos Por parte dos professores Por parte do corpo administrativo4
 
7.0%
Por parte dos alunos Por parte dos professores2
 
3.5%
Por parte do corpo administrativo1
 
1.8%
Por parte dos professores1
 
1.8%
(Missing)13
22.8%

Length

2022-05-31T15:05:36.977169image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:37.124776image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
por37
18.1%
parte37
18.1%
dos32
15.7%
alunos25
12.3%
não17
8.3%
consigo17
8.3%
definir17
8.3%
professores7
 
3.4%
do5
 
2.5%
corpo5
 
2.5%

Most occurring characters

ValueCountFrequency (%)
o179
15.3%
160
13.6%
r115
9.8%
s100
8.5%
a72
 
6.1%
e68
 
5.8%
i66
 
5.6%
n64
 
5.5%
d59
 
5.0%
p49
 
4.2%
Other values (11)241
20.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter959
81.8%
Space Separator160
 
13.6%
Uppercase Letter54
 
4.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o179
18.7%
r115
12.0%
s100
10.4%
a72
7.5%
e68
 
7.1%
i66
 
6.9%
n64
 
6.7%
d59
 
6.2%
p49
 
5.1%
t47
 
4.9%
Other values (8)140
14.6%
Uppercase Letter
ValueCountFrequency (%)
P37
68.5%
N17
31.5%
Space Separator
ValueCountFrequency (%)
160
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1013
86.4%
Common160
 
13.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
o179
17.7%
r115
11.4%
s100
9.9%
a72
 
7.1%
e68
 
6.7%
i66
 
6.5%
n64
 
6.3%
d59
 
5.8%
p49
 
4.8%
t47
 
4.6%
Other values (10)194
19.2%
Common
ValueCountFrequency (%)
160
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1156
98.6%
None17
 
1.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o179
15.5%
160
13.8%
r115
9.9%
s100
8.7%
a72
 
6.2%
e68
 
5.9%
i66
 
5.7%
n64
 
5.5%
d59
 
5.1%
p49
 
4.2%
Other values (10)224
19.4%
None
ValueCountFrequency (%)
ã17
100.0%

nmsocescol
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)14.3%
Missing43
Missing (%)75.4%
Memory size584.0 B
Sim
Não

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters42
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowSim
3rd rowNão
4th rowSim
5th rowNão

Common Values

ValueCountFrequency (%)
Sim9
 
15.8%
Não5
 
8.8%
(Missing)43
75.4%

Length

2022-05-31T15:05:37.276327image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:37.389026image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim9
64.3%
não5
35.7%

Most occurring characters

ValueCountFrequency (%)
S9
21.4%
i9
21.4%
m9
21.4%
N5
11.9%
ã5
11.9%
o5
11.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter28
66.7%
Uppercase Letter14
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i9
32.1%
m9
32.1%
ã5
17.9%
o5
17.9%
Uppercase Letter
ValueCountFrequency (%)
S9
64.3%
N5
35.7%

Most occurring scripts

ValueCountFrequency (%)
Latin42
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S9
21.4%
i9
21.4%
m9
21.4%
N5
11.9%
ã5
11.9%
o5
11.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII37
88.1%
None5
 
11.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S9
24.3%
i9
24.3%
m9
24.3%
N5
13.5%
o5
13.5%
None
ValueCountFrequency (%)
ã5
100.0%

acdscrmnscl
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct3
Distinct (%)20.0%
Missing42
Missing (%)73.7%
Memory size584.0 B
Não
Não sei
Sim

Length

Max length7
Median length3
Mean length4.333333333
Min length3

Characters and Unicode

Total characters65
Distinct characters9
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão
2nd rowNão
3rd rowNão sei
4th rowSim
5th rowNão

Common Values

ValueCountFrequency (%)
Não5
 
8.8%
Não sei5
 
8.8%
Sim5
 
8.8%
(Missing)42
73.7%

Length

2022-05-31T15:05:37.492749image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:37.626391image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não10
50.0%
sei5
25.0%
sim5
25.0%

Most occurring characters

ValueCountFrequency (%)
N10
15.4%
ã10
15.4%
o10
15.4%
i10
15.4%
5
7.7%
s5
7.7%
e5
7.7%
S5
7.7%
m5
7.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter45
69.2%
Uppercase Letter15
 
23.1%
Space Separator5
 
7.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
ã10
22.2%
o10
22.2%
i10
22.2%
s5
11.1%
e5
11.1%
m5
11.1%
Uppercase Letter
ValueCountFrequency (%)
N10
66.7%
S5
33.3%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin60
92.3%
Common5
 
7.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
N10
16.7%
ã10
16.7%
o10
16.7%
i10
16.7%
s5
8.3%
e5
8.3%
S5
8.3%
m5
8.3%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII55
84.6%
None10
 
15.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N10
18.2%
o10
18.2%
i10
18.2%
5
9.1%
s5
9.1%
e5
9.1%
S5
9.1%
m5
9.1%
None
ValueCountFrequency (%)
ã10
100.0%

profn
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)5.6%
Missing3
Missing (%)5.3%
Memory size584.0 B
Sim, apenas um(a) ou poucos
35 
Sim, vários(as)
14 
Não

Length

Max length27
Median length27
Mean length21.66666667
Min length3

Characters and Unicode

Total characters1170
Distinct characters20
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim, vários(as)
2nd rowSim, apenas um(a) ou poucos
3rd rowSim, apenas um(a) ou poucos
4th rowSim, vários(as)
5th rowSim, vários(as)

Common Values

ValueCountFrequency (%)
Sim, apenas um(a) ou poucos35
61.4%
Sim, vários(as)14
 
24.6%
Não5
 
8.8%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:37.734141image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:37.850791image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim49
23.6%
apenas35
16.8%
um(a35
16.8%
ou35
16.8%
poucos35
16.8%
vários(as14
 
6.7%
não5
 
2.4%

Most occurring characters

ValueCountFrequency (%)
154
13.2%
o124
10.6%
a119
10.2%
u105
9.0%
s98
 
8.4%
m84
 
7.2%
p70
 
6.0%
i63
 
5.4%
)49
 
4.2%
(49
 
4.2%
Other values (10)255
21.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter815
69.7%
Space Separator154
 
13.2%
Uppercase Letter54
 
4.6%
Close Punctuation49
 
4.2%
Open Punctuation49
 
4.2%
Other Punctuation49
 
4.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o124
15.2%
a119
14.6%
u105
12.9%
s98
12.0%
m84
10.3%
p70
8.6%
i63
7.7%
n35
 
4.3%
e35
 
4.3%
c35
 
4.3%
Other values (4)47
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
S49
90.7%
N5
 
9.3%
Space Separator
ValueCountFrequency (%)
154
100.0%
Close Punctuation
ValueCountFrequency (%)
)49
100.0%
Open Punctuation
ValueCountFrequency (%)
(49
100.0%
Other Punctuation
ValueCountFrequency (%)
,49
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin869
74.3%
Common301
 
25.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
o124
14.3%
a119
13.7%
u105
12.1%
s98
11.3%
m84
9.7%
p70
8.1%
i63
7.2%
S49
 
5.6%
n35
 
4.0%
e35
 
4.0%
Other values (6)87
10.0%
Common
ValueCountFrequency (%)
154
51.2%
)49
 
16.3%
(49
 
16.3%
,49
 
16.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII1151
98.4%
None19
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
154
13.4%
o124
10.8%
a119
10.3%
u105
9.1%
s98
8.5%
m84
 
7.3%
p70
 
6.1%
i63
 
5.5%
)49
 
4.3%
(49
 
4.3%
Other values (8)236
20.5%
None
ValueCountFrequency (%)
á14
73.7%
ã5
 
26.3%

profq
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)5.6%
Missing3
Missing (%)5.3%
Memory size584.0 B
Não
26 
Sim, apenas um(a) ou poucos
21 
Sim, vários

Length

Max length27
Median length11
Mean length13.37037037
Min length3

Characters and Unicode

Total characters722
Distinct characters20
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão
2nd rowNão
3rd rowSim, apenas um(a) ou poucos
4th rowNão
5th rowSim, apenas um(a) ou poucos

Common Values

ValueCountFrequency (%)
Não26
45.6%
Sim, apenas um(a) ou poucos21
36.8%
Sim, vários7
 
12.3%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:37.957505image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:38.067754image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim28
19.3%
não26
17.9%
apenas21
14.5%
um(a21
14.5%
ou21
14.5%
poucos21
14.5%
vários7
 
4.8%

Most occurring characters

ValueCountFrequency (%)
o96
13.3%
91
12.6%
a63
 
8.7%
u63
 
8.7%
m49
 
6.8%
s49
 
6.8%
p42
 
5.8%
i35
 
4.8%
S28
 
3.9%
,28
 
3.9%
Other values (10)178
24.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter507
70.2%
Space Separator91
 
12.6%
Uppercase Letter54
 
7.5%
Other Punctuation28
 
3.9%
Close Punctuation21
 
2.9%
Open Punctuation21
 
2.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o96
18.9%
a63
12.4%
u63
12.4%
m49
9.7%
s49
9.7%
p42
8.3%
i35
 
6.9%
ã26
 
5.1%
c21
 
4.1%
e21
 
4.1%
Other values (4)42
8.3%
Uppercase Letter
ValueCountFrequency (%)
S28
51.9%
N26
48.1%
Space Separator
ValueCountFrequency (%)
91
100.0%
Other Punctuation
ValueCountFrequency (%)
,28
100.0%
Close Punctuation
ValueCountFrequency (%)
)21
100.0%
Open Punctuation
ValueCountFrequency (%)
(21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin561
77.7%
Common161
 
22.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o96
17.1%
a63
11.2%
u63
11.2%
m49
8.7%
s49
8.7%
p42
7.5%
i35
 
6.2%
S28
 
5.0%
N26
 
4.6%
ã26
 
4.6%
Other values (6)84
15.0%
Common
ValueCountFrequency (%)
91
56.5%
,28
 
17.4%
)21
 
13.0%
(21
 
13.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII689
95.4%
None33
 
4.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o96
13.9%
91
13.2%
a63
9.1%
u63
9.1%
m49
 
7.1%
s49
 
7.1%
p42
 
6.1%
i35
 
5.1%
S28
 
4.1%
,28
 
4.1%
Other values (8)145
21.0%
None
ValueCountFrequency (%)
ã26
78.8%
á7
 
21.2%

proft
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)3.7%
Missing3
Missing (%)5.3%
Memory size584.0 B
Não
49 
Sim, apenas um(a) ou poucos

Length

Max length27
Median length3
Mean length5.222222222
Min length3

Characters and Unicode

Total characters282
Distinct characters17
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão
2nd rowNão
3rd rowNão
4th rowNão
5th rowNão

Common Values

ValueCountFrequency (%)
Não49
86.0%
Sim, apenas um(a) ou poucos5
 
8.8%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:38.181489image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:38.292156image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não49
66.2%
sim5
 
6.8%
apenas5
 
6.8%
um(a5
 
6.8%
ou5
 
6.8%
poucos5
 
6.8%

Most occurring characters

ValueCountFrequency (%)
o64
22.7%
N49
17.4%
ã49
17.4%
20
 
7.1%
u15
 
5.3%
a15
 
5.3%
m10
 
3.5%
p10
 
3.5%
s10
 
3.5%
,5
 
1.8%
Other values (7)35
12.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter193
68.4%
Uppercase Letter54
 
19.1%
Space Separator20
 
7.1%
Other Punctuation5
 
1.8%
Open Punctuation5
 
1.8%
Close Punctuation5
 
1.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o64
33.2%
ã49
25.4%
u15
 
7.8%
a15
 
7.8%
m10
 
5.2%
p10
 
5.2%
s10
 
5.2%
i5
 
2.6%
e5
 
2.6%
n5
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
N49
90.7%
S5
 
9.3%
Space Separator
ValueCountFrequency (%)
20
100.0%
Other Punctuation
ValueCountFrequency (%)
,5
100.0%
Open Punctuation
ValueCountFrequency (%)
(5
100.0%
Close Punctuation
ValueCountFrequency (%)
)5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin247
87.6%
Common35
 
12.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
o64
25.9%
N49
19.8%
ã49
19.8%
u15
 
6.1%
a15
 
6.1%
m10
 
4.0%
p10
 
4.0%
s10
 
4.0%
i5
 
2.0%
e5
 
2.0%
Other values (3)15
 
6.1%
Common
ValueCountFrequency (%)
20
57.1%
,5
 
14.3%
(5
 
14.3%
)5
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII233
82.6%
None49
 
17.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o64
27.5%
N49
21.0%
20
 
8.6%
u15
 
6.4%
a15
 
6.4%
m10
 
4.3%
p10
 
4.3%
s10
 
4.3%
,5
 
2.1%
i5
 
2.1%
Other values (6)30
12.9%
None
ValueCountFrequency (%)
ã49
100.0%

usaprep
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)7.5%
Missing4
Missing (%)7.0%
Memory size584.0 B
não
32 
Não sei o que é
11 
sim, uso atualmente
sim, já utilizei

Length

Max length19
Median length3
Mean length8.283018868
Min length3

Characters and Unicode

Total characters439
Distinct characters19
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão sei o que é
2nd rowNão sei o que é
3rd rownão
4th rowsim, uso atualmente
5th rowNão sei o que é

Common Values

ValueCountFrequency (%)
não32
56.1%
Não sei o que é11
 
19.3%
sim, uso atualmente6
 
10.5%
sim, já utilizei4
 
7.0%
(Missing)4
 
7.0%

Length

2022-05-31T15:05:38.396873image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:38.522538image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não43
36.8%
sei11
 
9.4%
o11
 
9.4%
que11
 
9.4%
é11
 
9.4%
sim10
 
8.5%
uso6
 
5.1%
atualmente6
 
5.1%
4
 
3.4%
utilizei4
 
3.4%

Most occurring characters

ValueCountFrequency (%)
64
14.6%
o60
13.7%
ã43
9.8%
n38
8.7%
e38
8.7%
i33
7.5%
u27
 
6.2%
s27
 
6.2%
m16
 
3.6%
t16
 
3.6%
Other values (9)77
17.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter354
80.6%
Space Separator64
 
14.6%
Uppercase Letter11
 
2.5%
Other Punctuation10
 
2.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o60
16.9%
ã43
12.1%
n38
10.7%
e38
10.7%
i33
9.3%
u27
7.6%
s27
7.6%
m16
 
4.5%
t16
 
4.5%
a12
 
3.4%
Other values (6)44
12.4%
Space Separator
ValueCountFrequency (%)
64
100.0%
Uppercase Letter
ValueCountFrequency (%)
N11
100.0%
Other Punctuation
ValueCountFrequency (%)
,10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin365
83.1%
Common74
 
16.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o60
16.4%
ã43
11.8%
n38
10.4%
e38
10.4%
i33
9.0%
u27
7.4%
s27
7.4%
m16
 
4.4%
t16
 
4.4%
a12
 
3.3%
Other values (7)55
15.1%
Common
ValueCountFrequency (%)
64
86.5%
,10
 
13.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII381
86.8%
None58
 
13.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
64
16.8%
o60
15.7%
n38
10.0%
e38
10.0%
i33
8.7%
u27
7.1%
s27
7.1%
m16
 
4.2%
t16
 
4.2%
a12
 
3.1%
Other values (6)50
13.1%
None
ValueCountFrequency (%)
ã43
74.1%
é11
 
19.0%
á4
 
6.9%

pqprep
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)3.7%
Missing3
Missing (%)5.3%
Memory size584.0 B
Sim
33 
Não
21 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters162
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão
2nd rowNão
3rd rowSim
4th rowSim
5th rowNão

Common Values

ValueCountFrequency (%)
Sim33
57.9%
Não21
36.8%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:38.639227image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:38.746979image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim33
61.1%
não21
38.9%

Most occurring characters

ValueCountFrequency (%)
S33
20.4%
i33
20.4%
m33
20.4%
N21
13.0%
ã21
13.0%
o21
13.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter108
66.7%
Uppercase Letter54
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i33
30.6%
m33
30.6%
ã21
19.4%
o21
19.4%
Uppercase Letter
ValueCountFrequency (%)
S33
61.1%
N21
38.9%

Most occurring scripts

ValueCountFrequency (%)
Latin162
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S33
20.4%
i33
20.4%
m33
20.4%
N21
13.0%
ã21
13.0%
o21
13.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII141
87.0%
None21
 
13.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S33
23.4%
i33
23.4%
m33
23.4%
N21
14.9%
o21
14.9%
None
ValueCountFrequency (%)
ã21
100.0%

medcontr
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)5.6%
Missing3
Missing (%)5.3%
Memory size584.0 B
Não
34 
Sim
18 
Preciso, mas não uso
 
2

Length

Max length20
Median length3
Mean length3.62962963
Min length3

Characters and Unicode

Total characters196
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão
2nd rowNão
3rd rowNão
4th rowNão
5th rowNão

Common Values

ValueCountFrequency (%)
Não34
59.6%
Sim18
31.6%
Preciso, mas não uso2
 
3.5%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:38.850661image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:38.970339image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não36
60.0%
sim18
30.0%
preciso2
 
3.3%
mas2
 
3.3%
uso2
 
3.3%

Most occurring characters

ValueCountFrequency (%)
o40
20.4%
ã36
18.4%
N34
17.3%
i20
10.2%
m20
10.2%
S18
9.2%
s6
 
3.1%
6
 
3.1%
P2
 
1.0%
r2
 
1.0%
Other values (6)12
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter134
68.4%
Uppercase Letter54
27.6%
Space Separator6
 
3.1%
Other Punctuation2
 
1.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o40
29.9%
ã36
26.9%
i20
14.9%
m20
14.9%
s6
 
4.5%
r2
 
1.5%
e2
 
1.5%
c2
 
1.5%
a2
 
1.5%
n2
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
N34
63.0%
S18
33.3%
P2
 
3.7%
Space Separator
ValueCountFrequency (%)
6
100.0%
Other Punctuation
ValueCountFrequency (%)
,2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin188
95.9%
Common8
 
4.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o40
21.3%
ã36
19.1%
N34
18.1%
i20
10.6%
m20
10.6%
S18
9.6%
s6
 
3.2%
P2
 
1.1%
r2
 
1.1%
e2
 
1.1%
Other values (4)8
 
4.3%
Common
ValueCountFrequency (%)
6
75.0%
,2
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII160
81.6%
None36
 
18.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o40
25.0%
N34
21.2%
i20
12.5%
m20
12.5%
S18
11.2%
s6
 
3.8%
6
 
3.8%
P2
 
1.2%
r2
 
1.2%
e2
 
1.2%
Other values (5)10
 
6.2%
None
ValueCountFrequency (%)
ã36
100.0%

medhiv
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)3.7%
Missing3
Missing (%)5.3%
Memory size584.0 B
Não
47 
Sim

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters162
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão
2nd rowNão
3rd rowNão
4th rowNão
5th rowNão

Common Values

ValueCountFrequency (%)
Não47
82.5%
Sim7
 
12.3%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:39.075060image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:39.190786image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não47
87.0%
sim7
 
13.0%

Most occurring characters

ValueCountFrequency (%)
N47
29.0%
ã47
29.0%
o47
29.0%
S7
 
4.3%
i7
 
4.3%
m7
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter108
66.7%
Uppercase Letter54
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
ã47
43.5%
o47
43.5%
i7
 
6.5%
m7
 
6.5%
Uppercase Letter
ValueCountFrequency (%)
N47
87.0%
S7
 
13.0%

Most occurring scripts

ValueCountFrequency (%)
Latin162
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N47
29.0%
ã47
29.0%
o47
29.0%
S7
 
4.3%
i7
 
4.3%
m7
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII115
71.0%
None47
29.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N47
40.9%
o47
40.9%
S7
 
6.1%
i7
 
6.1%
m7
 
6.1%
None
ValueCountFrequency (%)
ã47
100.0%

pilseg
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)30.0%
Missing47
Missing (%)82.5%
Memory size584.0 B
Não
Sim
Prefiro não responder

Length

Max length21
Median length3
Mean length4.8
Min length3

Characters and Unicode

Total characters48
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)10.0%

Sample

1st rowNão
2nd rowNão
3rd rowNão
4th rowPrefiro não responder
5th rowSim

Common Values

ValueCountFrequency (%)
Não6
 
10.5%
Sim3
 
5.3%
Prefiro não responder1
 
1.8%
(Missing)47
82.5%

Length

2022-05-31T15:05:39.293517image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:39.411160image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não7
58.3%
sim3
25.0%
prefiro1
 
8.3%
responder1
 
8.3%

Most occurring characters

ValueCountFrequency (%)
o9
18.8%
ã7
14.6%
N6
12.5%
i4
8.3%
r4
8.3%
S3
 
6.2%
m3
 
6.2%
e3
 
6.2%
2
 
4.2%
n2
 
4.2%
Other values (5)5
10.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter36
75.0%
Uppercase Letter10
 
20.8%
Space Separator2
 
4.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o9
25.0%
ã7
19.4%
i4
11.1%
r4
11.1%
m3
 
8.3%
e3
 
8.3%
n2
 
5.6%
f1
 
2.8%
s1
 
2.8%
p1
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
N6
60.0%
S3
30.0%
P1
 
10.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin46
95.8%
Common2
 
4.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
o9
19.6%
ã7
15.2%
N6
13.0%
i4
8.7%
r4
8.7%
S3
 
6.5%
m3
 
6.5%
e3
 
6.5%
n2
 
4.3%
P1
 
2.2%
Other values (4)4
8.7%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII41
85.4%
None7
 
14.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o9
22.0%
N6
14.6%
i4
9.8%
r4
9.8%
S3
 
7.3%
m3
 
7.3%
e3
 
7.3%
2
 
4.9%
n2
 
4.9%
P1
 
2.4%
Other values (4)4
9.8%
None
ValueCountFrequency (%)
ã7
100.0%

freqmed
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)7.4%
Missing3
Missing (%)5.3%
Memory size584.0 B
Vou mais de duas vezes ao ano
24 
Raramente vou
15 
Pelo menos uma ou duas vezes ao ano
12 
Nunca vou

Length

Max length35
Median length29
Mean length24.77777778
Min length9

Characters and Unicode

Total characters1338
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowVou mais de duas vezes ao ano
2nd rowVou mais de duas vezes ao ano
3rd rowVou mais de duas vezes ao ano
4th rowRaramente vou
5th rowRaramente vou

Common Values

ValueCountFrequency (%)
Vou mais de duas vezes ao ano24
42.1%
Raramente vou15
26.3%
Pelo menos uma ou duas vezes ao ano12
21.1%
Nunca vou3
 
5.3%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:39.519871image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:39.646532image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
vou42
14.0%
duas36
12.0%
vezes36
12.0%
ao36
12.0%
ano36
12.0%
mais24
8.0%
de24
8.0%
raramente15
 
5.0%
pelo12
 
4.0%
menos12
 
4.0%
Other values (3)27
9.0%

Most occurring characters

ValueCountFrequency (%)
246
18.4%
a177
13.2%
e150
11.2%
o150
11.2%
s108
8.1%
u105
7.8%
n66
 
4.9%
m63
 
4.7%
d60
 
4.5%
v54
 
4.0%
Other values (10)159
11.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1038
77.6%
Space Separator246
 
18.4%
Uppercase Letter54
 
4.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a177
17.1%
e150
14.5%
o150
14.5%
s108
10.4%
u105
10.1%
n66
 
6.4%
m63
 
6.1%
d60
 
5.8%
v54
 
5.2%
z36
 
3.5%
Other values (5)69
 
6.6%
Uppercase Letter
ValueCountFrequency (%)
V24
44.4%
R15
27.8%
P12
22.2%
N3
 
5.6%
Space Separator
ValueCountFrequency (%)
246
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1092
81.6%
Common246
 
18.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a177
16.2%
e150
13.7%
o150
13.7%
s108
9.9%
u105
9.6%
n66
 
6.0%
m63
 
5.8%
d60
 
5.5%
v54
 
4.9%
z36
 
3.3%
Other values (9)123
11.3%
Common
ValueCountFrequency (%)
246
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1338
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
246
18.4%
a177
13.2%
e150
11.2%
o150
11.2%
s108
8.1%
u105
7.8%
n66
 
4.9%
m63
 
4.7%
d60
 
4.5%
v54
 
4.0%
Other values (10)159
11.9%

freqdent
Categorical

HIGH CORRELATION
MISSING

Distinct5
Distinct (%)9.3%
Missing3
Missing (%)5.3%
Memory size584.0 B
Raramente vou
24 
Pelo menos uma ou duas vezes ao ano
14 
Vou mais de duas vezes ao ano
10 
Nunca vou
9XHk43YAJ+xohcluw6H2g+GVj/u8qYu9/YnuG3tDGyswSNyODpLMVOx5dFOQLbia0K5JrSgu7UG7ihQjPLArM18SIM5p4lSI6fSCtTebKb1jgQzYgYjpGi7+xdmYAmqdHxGPkBbpycK2w2N1FvkH9gYv4SHr55AGFPFA9A0qUYDsY0N/ovUFWKm87XyZAQcNGJqxcnK5MzaHEtWDUKMnXbnomL2sY38zTqFxw8UvpTRIoX7tyz8+IP9tGgZa7XzpgGsmcVXREaVyfF/kXfoaJIA+nvQ2hjjJZqG+Fyfi/LfNBRQul/Rp0YaWb9koxOtyjuNWda43k6gqqXL26WTl
 
1

Length

Max length340
Median length35
Mean length27.35185185
Min length9

Characters and Unicode

Total characters1477
Distinct characters65
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st rowVou mais de duas vezes ao ano
2nd rowNunca vou
3rd rowRaramente vou
4th rowRaramente vou
5th rowPelo menos uma ou duas vezes ao ano

Common Values

ValueCountFrequency (%)
Raramente vou24
42.1%
Pelo menos uma ou duas vezes ao ano14
24.6%
Vou mais de duas vezes ao ano10
17.5%
Nunca vou5
 
8.8%
9XHk43YAJ+xohcluw6H2g+GVj/u8qYu9/YnuG3tDGyswSNyODpLMVOx5dFOQLbia0K5JrSgu7UG7ihQjPLArM18SIM5p4lSI6fSCtTebKb1jgQzYgYjpGi7+xdmYAmqdHxGPkBbpycK2w2N1FvkH9gYv4SHr55AGFPFA9A0qUYDsY0N/ovUFWKm87XyZAQcNGJqxcnK5MzaHEtWDUKMnXbnomL2sY38zTqFxw8UvpTRIoX7tyz8+IP9tGgZa7XzpgGsmcVXREaVyfF/kXfoaJIA+nvQ2hjjJZqG+Fyfi/LfNBRQul/Rp0YaWb9koxOtyjuNWda43k6gqqXL26WTl1
 
1.8%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:39.777220image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:39.919799image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
vou39
16.2%
raramente24
10.0%
duas24
10.0%
vezes24
10.0%
ao24
10.0%
ano24
10.0%
pelo14
 
5.8%
menos14
 
5.8%
uma14
 
5.8%
ou14
 
5.8%
Other values (4)26
10.8%

Most occurring characters

ValueCountFrequency (%)
187
12.7%
a156
 
10.6%
o135
 
9.1%
e135
 
9.1%
u103
 
7.0%
s76
 
5.1%
n72
 
4.9%
m67
 
4.5%
v58
 
3.9%
d38
 
2.6%
Other values (55)450
30.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1037
70.2%
Uppercase Letter192
 
13.0%
Space Separator187
 
12.7%
Decimal Number49
 
3.3%
Other Punctuation6
 
0.4%
Math Symbol6
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a156
15.0%
o135
13.0%
e135
13.0%
u103
9.9%
s76
7.3%
n72
6.9%
m67
6.5%
v58
 
5.6%
d38
 
3.7%
t30
 
2.9%
Other values (16)167
16.1%
Uppercase Letter
ValueCountFrequency (%)
R28
14.6%
P18
 
9.4%
V14
 
7.3%
G11
 
5.7%
Y11
 
5.7%
N11
 
5.7%
X8
 
4.2%
F8
 
4.2%
A8
 
4.2%
L6
 
3.1%
Other values (16)69
35.9%
Decimal Number
ValueCountFrequency (%)
76
12.2%
86
12.2%
56
12.2%
96
12.2%
26
12.2%
04
8.2%
64
8.2%
34
8.2%
44
8.2%
13
6.1%
Space Separator
ValueCountFrequency (%)
187
100.0%
Other Punctuation
ValueCountFrequency (%)
/6
100.0%
Math Symbol
ValueCountFrequency (%)
+6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1229
83.2%
Common248
 
16.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a156
12.7%
o135
 
11.0%
e135
 
11.0%
u103
 
8.4%
s76
 
6.2%
n72
 
5.9%
m67
 
5.5%
v58
 
4.7%
d38
 
3.1%
t30
 
2.4%
Other values (42)359
29.2%
Common
ValueCountFrequency (%)
187
75.4%
/6
 
2.4%
76
 
2.4%
86
 
2.4%
56
 
2.4%
96
 
2.4%
26
 
2.4%
+6
 
2.4%
04
 
1.6%
64
 
1.6%
Other values (3)11
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII1477
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
187
12.7%
a156
 
10.6%
o135
 
9.1%
e135
 
9.1%
u103
 
7.0%
s76
 
5.1%
n72
 
4.9%
m67
 
4.5%
v58
 
3.9%
d38
 
2.6%
Other values (55)450
30.5%

exhiv
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)3.7%
Missing3
Missing (%)5.3%
Memory size584.0 B
Sim
45 
Não

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters162
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowSim
3rd rowSim
4th rowSim
5th rowSim

Common Values

ValueCountFrequency (%)
Sim45
78.9%
Não9
 
15.8%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:40.096862image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:40.203617image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim45
83.3%
não9
 
16.7%

Most occurring characters

ValueCountFrequency (%)
S45
27.8%
i45
27.8%
m45
27.8%
N9
 
5.6%
ã9
 
5.6%
o9
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter108
66.7%
Uppercase Letter54
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i45
41.7%
m45
41.7%
ã9
 
8.3%
o9
 
8.3%
Uppercase Letter
ValueCountFrequency (%)
S45
83.3%
N9
 
16.7%

Most occurring scripts

ValueCountFrequency (%)
Latin162
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S45
27.8%
i45
27.8%
m45
27.8%
N9
 
5.6%
ã9
 
5.6%
o9
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII153
94.4%
None9
 
5.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S45
29.4%
i45
29.4%
m45
29.4%
N9
 
5.9%
o9
 
5.9%
None
ValueCountFrequency (%)
ã9
100.0%

reshiv
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)4.5%
Missing13
Missing (%)22.8%
Memory size584.0 B
Negativo
37 
Positivo

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters352
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNegativo
2nd rowNegativo
3rd rowNegativo
4th rowNegativo
5th rowNegativo

Common Values

ValueCountFrequency (%)
Negativo37
64.9%
Positivo7
 
12.3%
(Missing)13
 
22.8%

Length

2022-05-31T15:05:40.300316image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:40.419280image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
negativo37
84.1%
positivo7
 
15.9%

Most occurring characters

ValueCountFrequency (%)
i51
14.5%
o51
14.5%
t44
12.5%
v44
12.5%
N37
10.5%
e37
10.5%
g37
10.5%
a37
10.5%
P7
 
2.0%
s7
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter308
87.5%
Uppercase Letter44
 
12.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i51
16.6%
o51
16.6%
t44
14.3%
v44
14.3%
e37
12.0%
g37
12.0%
a37
12.0%
s7
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
N37
84.1%
P7
 
15.9%

Most occurring scripts

ValueCountFrequency (%)
Latin352
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i51
14.5%
o51
14.5%
t44
12.5%
v44
12.5%
N37
10.5%
e37
10.5%
g37
10.5%
a37
10.5%
P7
 
2.0%
s7
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII352
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i51
14.5%
o51
14.5%
t44
12.5%
v44
12.5%
N37
10.5%
e37
10.5%
g37
10.5%
a37
10.5%
P7
 
2.0%
s7
 
2.0%

exsif
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)5.6%
Missing3
Missing (%)5.3%
Memory size584.0 B
Sim
42 
Não
11 
Prefiro não responder
 
1

Length

Max length21
Median length3
Mean length3.333333333
Min length3

Characters and Unicode

Total characters180
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st rowPrefiro não responder
2nd rowSim
3rd rowSim
4th rowSim
5th rowNão

Common Values

ValueCountFrequency (%)
Sim42
73.7%
Não11
 
19.3%
Prefiro não responder1
 
1.8%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:40.529985image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:40.648666image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim42
75.0%
não12
 
21.4%
prefiro1
 
1.8%
responder1
 
1.8%

Most occurring characters

ValueCountFrequency (%)
i43
23.9%
S42
23.3%
m42
23.3%
o14
 
7.8%
ã12
 
6.7%
N11
 
6.1%
r4
 
2.2%
e3
 
1.7%
2
 
1.1%
n2
 
1.1%
Other values (5)5
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter124
68.9%
Uppercase Letter54
30.0%
Space Separator2
 
1.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i43
34.7%
m42
33.9%
o14
 
11.3%
ã12
 
9.7%
r4
 
3.2%
e3
 
2.4%
n2
 
1.6%
f1
 
0.8%
s1
 
0.8%
p1
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
S42
77.8%
N11
 
20.4%
P1
 
1.9%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin178
98.9%
Common2
 
1.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
i43
24.2%
S42
23.6%
m42
23.6%
o14
 
7.9%
ã12
 
6.7%
N11
 
6.2%
r4
 
2.2%
e3
 
1.7%
n2
 
1.1%
P1
 
0.6%
Other values (4)4
 
2.2%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII168
93.3%
None12
 
6.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i43
25.6%
S42
25.0%
m42
25.0%
o14
 
8.3%
N11
 
6.5%
r4
 
2.4%
e3
 
1.8%
2
 
1.2%
n2
 
1.2%
P1
 
0.6%
Other values (4)4
 
2.4%
None
ValueCountFrequency (%)
ã12
100.0%

ressif
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)4.9%
Missing16
Missing (%)28.1%
Memory size584.0 B
Negativo
28 
Positivo
13 

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters328
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNegativo
2nd rowNegativo
3rd rowNegativo
4th rowPositivo
5th rowPositivo

Common Values

ValueCountFrequency (%)
Negativo28
49.1%
Positivo13
22.8%
(Missing)16
28.1%

Length

2022-05-31T15:05:40.751387image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:40.874058image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
negativo28
68.3%
positivo13
31.7%

Most occurring characters

ValueCountFrequency (%)
i54
16.5%
o54
16.5%
t41
12.5%
v41
12.5%
N28
8.5%
e28
8.5%
g28
8.5%
a28
8.5%
P13
 
4.0%
s13
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter287
87.5%
Uppercase Letter41
 
12.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i54
18.8%
o54
18.8%
t41
14.3%
v41
14.3%
e28
9.8%
g28
9.8%
a28
9.8%
s13
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
N28
68.3%
P13
31.7%

Most occurring scripts

ValueCountFrequency (%)
Latin328
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i54
16.5%
o54
16.5%
t41
12.5%
v41
12.5%
N28
8.5%
e28
8.5%
g28
8.5%
a28
8.5%
P13
 
4.0%
s13
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII328
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i54
16.5%
o54
16.5%
t41
12.5%
v41
12.5%
N28
8.5%
e28
8.5%
g28
8.5%
a28
8.5%
P13
 
4.0%
s13
 
4.0%

exhep
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)3.7%
Missing3
Missing (%)5.3%
Memory size584.0 B
Sim
38 
Não
16 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters162
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão
2nd rowSim
3rd rowNão
4th rowSim
5th rowNão

Common Values

ValueCountFrequency (%)
Sim38
66.7%
Não16
28.1%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:40.974791image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:41.082506image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim38
70.4%
não16
29.6%

Most occurring characters

ValueCountFrequency (%)
S38
23.5%
i38
23.5%
m38
23.5%
N16
9.9%
ã16
9.9%
o16
9.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter108
66.7%
Uppercase Letter54
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i38
35.2%
m38
35.2%
ã16
14.8%
o16
14.8%
Uppercase Letter
ValueCountFrequency (%)
S38
70.4%
N16
29.6%

Most occurring scripts

ValueCountFrequency (%)
Latin162
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S38
23.5%
i38
23.5%
m38
23.5%
N16
9.9%
ã16
9.9%
o16
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII146
90.1%
None16
 
9.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S38
26.0%
i38
26.0%
m38
26.0%
N16
11.0%
o16
11.0%
None
ValueCountFrequency (%)
ã16
100.0%

reshep
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)5.4%
Missing20
Missing (%)35.1%
Memory size584.0 B
Negativo
36 
Positivo
 
1

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters296
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)2.7%

Sample

1st rowNegativo
2nd rowNegativo
3rd rowNegativo
4th rowNegativo
5th rowNegativo

Common Values

ValueCountFrequency (%)
Negativo36
63.2%
Positivo1
 
1.8%
(Missing)20
35.1%

Length

2022-05-31T15:05:41.182195image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:41.323814image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
negativo36
97.3%
positivo1
 
2.7%

Most occurring characters

ValueCountFrequency (%)
i38
12.8%
o38
12.8%
t37
12.5%
v37
12.5%
N36
12.2%
e36
12.2%
g36
12.2%
a36
12.2%
P1
 
0.3%
s1
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter259
87.5%
Uppercase Letter37
 
12.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i38
14.7%
o38
14.7%
t37
14.3%
v37
14.3%
e36
13.9%
g36
13.9%
a36
13.9%
s1
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
N36
97.3%
P1
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
Latin296
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i38
12.8%
o38
12.8%
t37
12.5%
v37
12.5%
N36
12.2%
e36
12.2%
g36
12.2%
a36
12.2%
P1
 
0.3%
s1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII296
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i38
12.8%
o38
12.8%
t37
12.5%
v37
12.5%
N36
12.2%
e36
12.2%
g36
12.2%
a36
12.2%
P1
 
0.3%
s1
 
0.3%

exist
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)5.6%
Missing3
Missing (%)5.3%
Memory size584.0 B
Não
26 
Sim
26 
Prefiro não responder
 
2

Length

Max length21
Median length3
Mean length3.666666667
Min length3

Characters and Unicode

Total characters198
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão
2nd rowSim
3rd rowSim
4th rowSim
5th rowNão

Common Values

ValueCountFrequency (%)
Não26
45.6%
Sim26
45.6%
Prefiro não responder2
 
3.5%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:41.449523image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:41.573149image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não28
48.3%
sim26
44.8%
prefiro2
 
3.4%
responder2
 
3.4%

Most occurring characters

ValueCountFrequency (%)
o32
16.2%
ã28
14.1%
i28
14.1%
N26
13.1%
S26
13.1%
m26
13.1%
r8
 
4.0%
e6
 
3.0%
4
 
2.0%
n4
 
2.0%
Other values (5)10
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter140
70.7%
Uppercase Letter54
 
27.3%
Space Separator4
 
2.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o32
22.9%
ã28
20.0%
i28
20.0%
m26
18.6%
r8
 
5.7%
e6
 
4.3%
n4
 
2.9%
f2
 
1.4%
s2
 
1.4%
p2
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
N26
48.1%
S26
48.1%
P2
 
3.7%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin194
98.0%
Common4
 
2.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o32
16.5%
ã28
14.4%
i28
14.4%
N26
13.4%
S26
13.4%
m26
13.4%
r8
 
4.1%
e6
 
3.1%
n4
 
2.1%
P2
 
1.0%
Other values (4)8
 
4.1%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII170
85.9%
None28
 
14.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o32
18.8%
i28
16.5%
N26
15.3%
S26
15.3%
m26
15.3%
r8
 
4.7%
e6
 
3.5%
4
 
2.4%
n4
 
2.4%
P2
 
1.2%
Other values (4)8
 
4.7%
None
ValueCountFrequency (%)
ã28
100.0%

resist
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)7.7%
Missing31
Missing (%)54.4%
Memory size584.0 B
Negativo
25 
Positivo
 
1

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters208
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)3.8%

Sample

1st rowNegativo
2nd rowNegativo
3rd rowNegativo
4th rowNegativo
5th rowPositivo

Common Values

ValueCountFrequency (%)
Negativo25
43.9%
Positivo1
 
1.8%
(Missing)31
54.4%

Length

2022-05-31T15:05:41.673878image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:41.776603image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
negativo25
96.2%
positivo1
 
3.8%

Most occurring characters

ValueCountFrequency (%)
i27
13.0%
o27
13.0%
t26
12.5%
v26
12.5%
N25
12.0%
e25
12.0%
g25
12.0%
a25
12.0%
P1
 
0.5%
s1
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter182
87.5%
Uppercase Letter26
 
12.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i27
14.8%
o27
14.8%
t26
14.3%
v26
14.3%
e25
13.7%
g25
13.7%
a25
13.7%
s1
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
N25
96.2%
P1
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
Latin208
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i27
13.0%
o27
13.0%
t26
12.5%
v26
12.5%
N25
12.0%
e25
12.0%
g25
12.0%
a25
12.0%
P1
 
0.5%
s1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII208
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i27
13.0%
o27
13.0%
t26
12.5%
v26
12.5%
N25
12.0%
e25
12.0%
g25
12.0%
a25
12.0%
P1
 
0.5%
s1
 
0.5%

hormo
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)5.6%
Missing3
Missing (%)5.3%
Memory size584.0 B
Não
24 
Sim
21 
Já utilizei no passado, agora não uso mais

Length

Max length42
Median length3
Mean length9.5
Min length3

Characters and Unicode

Total characters513
Distinct characters22
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão
2nd rowNão
3rd rowNão
4th rowNão
5th rowSim

Common Values

ValueCountFrequency (%)
Não24
42.1%
Sim21
36.8%
Já utilizei no passado, agora não uso mais9
 
15.8%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:41.870353image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:41.994021image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não33
28.2%
sim21
17.9%
9
 
7.7%
utilizei9
 
7.7%
no9
 
7.7%
passado9
 
7.7%
agora9
 
7.7%
uso9
 
7.7%
mais9
 
7.7%

Most occurring characters

ValueCountFrequency (%)
o69
13.5%
63
12.3%
i57
11.1%
a45
 
8.8%
s36
 
7.0%
ã33
 
6.4%
m30
 
5.8%
N24
 
4.7%
S21
 
4.1%
u18
 
3.5%
Other values (12)117
22.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter387
75.4%
Space Separator63
 
12.3%
Uppercase Letter54
 
10.5%
Other Punctuation9
 
1.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o69
17.8%
i57
14.7%
a45
11.6%
s36
9.3%
ã33
8.5%
m30
7.8%
u18
 
4.7%
n18
 
4.7%
p9
 
2.3%
g9
 
2.3%
Other values (7)63
16.3%
Uppercase Letter
ValueCountFrequency (%)
N24
44.4%
S21
38.9%
J9
 
16.7%
Space Separator
ValueCountFrequency (%)
63
100.0%
Other Punctuation
ValueCountFrequency (%)
,9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin441
86.0%
Common72
 
14.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o69
15.6%
i57
12.9%
a45
10.2%
s36
 
8.2%
ã33
 
7.5%
m30
 
6.8%
N24
 
5.4%
S21
 
4.8%
u18
 
4.1%
n18
 
4.1%
Other values (10)90
20.4%
Common
ValueCountFrequency (%)
63
87.5%
,9
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII471
91.8%
None42
 
8.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o69
14.6%
63
13.4%
i57
12.1%
a45
9.6%
s36
 
7.6%
m30
 
6.4%
N24
 
5.1%
S21
 
4.5%
u18
 
3.8%
n18
 
3.8%
Other values (10)90
19.1%
None
ValueCountFrequency (%)
ã33
78.6%
á9
 
21.4%

fimhormo
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)10.0%
Missing37
Missing (%)64.9%
Memory size584.0 B
Para terapia hormonal (mudanças corporais)
18 
Para aceleração metabólica (ganho muscular, uso dietário)

Length

Max length57
Median length42
Mean length43.5
Min length42

Characters and Unicode

Total characters870
Distinct characters26
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPara terapia hormonal (mudanças corporais)
2nd rowPara aceleração metabólica (ganho muscular, uso dietário)
3rd rowPara aceleração metabólica (ganho muscular, uso dietário)
4th rowPara terapia hormonal (mudanças corporais)
5th rowPara terapia hormonal (mudanças corporais)

Common Values

ValueCountFrequency (%)
Para terapia hormonal (mudanças corporais)18
31.6%
Para aceleração metabólica (ganho muscular, uso dietário)2
 
3.5%
(Missing)37
64.9%

Length

2022-05-31T15:05:42.132654image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:42.278826image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
para20
19.2%
terapia18
17.3%
hormonal18
17.3%
mudanças18
17.3%
corporais18
17.3%
aceleração2
 
1.9%
metabólica2
 
1.9%
ganho2
 
1.9%
muscular2
 
1.9%
uso2
 
1.9%

Most occurring characters

ValueCountFrequency (%)
a160
18.4%
r98
11.3%
84
 
9.7%
o80
 
9.2%
i42
 
4.8%
s40
 
4.6%
m40
 
4.6%
n38
 
4.4%
p36
 
4.1%
e26
 
3.0%
Other values (16)226
26.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter724
83.2%
Space Separator84
 
9.7%
Uppercase Letter20
 
2.3%
Close Punctuation20
 
2.3%
Open Punctuation20
 
2.3%
Other Punctuation2
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a160
22.1%
r98
13.5%
o80
11.0%
i42
 
5.8%
s40
 
5.5%
m40
 
5.5%
n38
 
5.2%
p36
 
5.0%
e26
 
3.6%
l24
 
3.3%
Other values (11)140
19.3%
Space Separator
ValueCountFrequency (%)
84
100.0%
Uppercase Letter
ValueCountFrequency (%)
P20
100.0%
Close Punctuation
ValueCountFrequency (%)
)20
100.0%
Open Punctuation
ValueCountFrequency (%)
(20
100.0%
Other Punctuation
ValueCountFrequency (%)
,2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin744
85.5%
Common126
 
14.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a160
21.5%
r98
13.2%
o80
10.8%
i42
 
5.6%
s40
 
5.4%
m40
 
5.4%
n38
 
5.1%
p36
 
4.8%
e26
 
3.5%
l24
 
3.2%
Other values (12)160
21.5%
Common
ValueCountFrequency (%)
84
66.7%
)20
 
15.9%
(20
 
15.9%
,2
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII844
97.0%
None26
 
3.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a160
19.0%
r98
11.6%
84
10.0%
o80
 
9.5%
i42
 
5.0%
s40
 
4.7%
m40
 
4.7%
n38
 
4.5%
p36
 
4.3%
e26
 
3.1%
Other values (12)200
23.7%
None
ValueCountFrequency (%)
ç20
76.9%
ã2
 
7.7%
ó2
 
7.7%
á2
 
7.7%

medprehorm
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)10.0%
Missing37
Missing (%)64.9%
Memory size584.0 B
Não
12 
Sim

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters60
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowNão
3rd rowNão
4th rowNão
5th rowNão

Common Values

ValueCountFrequency (%)
Não12
 
21.1%
Sim8
 
14.0%
(Missing)37
64.9%

Length

2022-05-31T15:05:42.395512image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:42.521220image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não12
60.0%
sim8
40.0%

Most occurring characters

ValueCountFrequency (%)
N12
20.0%
ã12
20.0%
o12
20.0%
S8
13.3%
i8
13.3%
m8
13.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter40
66.7%
Uppercase Letter20
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
ã12
30.0%
o12
30.0%
i8
20.0%
m8
20.0%
Uppercase Letter
ValueCountFrequency (%)
N12
60.0%
S8
40.0%

Most occurring scripts

ValueCountFrequency (%)
Latin60
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N12
20.0%
ã12
20.0%
o12
20.0%
S8
13.3%
i8
13.3%
m8
13.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII48
80.0%
None12
 
20.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N12
25.0%
o12
25.0%
S8
16.7%
i8
16.7%
m8
16.7%
None
ValueCountFrequency (%)
ã12
100.0%

silic
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)3.7%
Missing3
Missing (%)5.3%
Memory size584.0 B
Não
45 
Sim

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters162
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão
2nd rowSim
3rd rowNão
4th rowNão
5th rowNão

Common Values

ValueCountFrequency (%)
Não45
78.9%
Sim9
 
15.8%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:42.624899image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:42.728621image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não45
83.3%
sim9
 
16.7%

Most occurring characters

ValueCountFrequency (%)
N45
27.8%
ã45
27.8%
o45
27.8%
S9
 
5.6%
i9
 
5.6%
m9
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter108
66.7%
Uppercase Letter54
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
ã45
41.7%
o45
41.7%
i9
 
8.3%
m9
 
8.3%
Uppercase Letter
ValueCountFrequency (%)
N45
83.3%
S9
 
16.7%

Most occurring scripts

ValueCountFrequency (%)
Latin162
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N45
27.8%
ã45
27.8%
o45
27.8%
S9
 
5.6%
i9
 
5.6%
m9
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII117
72.2%
None45
 
27.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N45
38.5%
o45
38.5%
S9
 
7.7%
i9
 
7.7%
m9
 
7.7%
None
ValueCountFrequency (%)
ã45
100.0%

fumo
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)5.6%
Missing3
Missing (%)5.3%
Memory size584.0 B
Sim
31 
Não
19 
Só às vezes, raramente.

Length

Max length23
Median length3
Mean length4.481481481
Min length3

Characters and Unicode

Total characters242
Distinct characters19
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSó às vezes, raramente.
2nd rowSim
3rd rowSim
4th rowSim
5th rowNão

Common Values

ValueCountFrequency (%)
Sim31
54.4%
Não19
33.3%
Só às vezes, raramente.4
 
7.0%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:42.829353image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:42.957012image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim31
47.0%
não19
28.8%
4
 
6.1%
às4
 
6.1%
vezes4
 
6.1%
raramente4
 
6.1%

Most occurring characters

ValueCountFrequency (%)
S35
14.5%
m35
14.5%
i31
12.8%
N19
7.9%
ã19
7.9%
o19
7.9%
e16
 
6.6%
12
 
5.0%
a8
 
3.3%
r8
 
3.3%
Other values (9)40
16.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter168
69.4%
Uppercase Letter54
 
22.3%
Space Separator12
 
5.0%
Other Punctuation8
 
3.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
m35
20.8%
i31
18.5%
ã19
11.3%
o19
11.3%
e16
9.5%
a8
 
4.8%
r8
 
4.8%
s8
 
4.8%
v4
 
2.4%
z4
 
2.4%
Other values (4)16
9.5%
Uppercase Letter
ValueCountFrequency (%)
S35
64.8%
N19
35.2%
Other Punctuation
ValueCountFrequency (%)
,4
50.0%
.4
50.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin222
91.7%
Common20
 
8.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
S35
15.8%
m35
15.8%
i31
14.0%
N19
8.6%
ã19
8.6%
o19
8.6%
e16
7.2%
a8
 
3.6%
r8
 
3.6%
s8
 
3.6%
Other values (6)24
10.8%
Common
ValueCountFrequency (%)
12
60.0%
,4
 
20.0%
.4
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII215
88.8%
None27
 
11.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S35
16.3%
m35
16.3%
i31
14.4%
N19
8.8%
o19
8.8%
e16
7.4%
12
 
5.6%
a8
 
3.7%
r8
 
3.7%
s8
 
3.7%
Other values (6)24
11.2%
None
ValueCountFrequency (%)
ã19
70.4%
à4
 
14.8%
ó4
 
14.8%

frequs
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)3.7%
Missing3
Missing (%)5.3%
Memory size584.0 B
Sim
36 
Não
18 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters162
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowNão
3rd rowSim
4th rowSim
5th rowSim

Common Values

ValueCountFrequency (%)
Sim36
63.2%
Não18
31.6%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:43.064761image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:43.179417image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim36
66.7%
não18
33.3%

Most occurring characters

ValueCountFrequency (%)
S36
22.2%
i36
22.2%
m36
22.2%
N18
11.1%
ã18
11.1%
o18
11.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter108
66.7%
Uppercase Letter54
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i36
33.3%
m36
33.3%
ã18
16.7%
o18
16.7%
Uppercase Letter
ValueCountFrequency (%)
S36
66.7%
N18
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin162
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S36
22.2%
i36
22.2%
m36
22.2%
N18
11.1%
ã18
11.1%
o18
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII144
88.9%
None18
 
11.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S36
25.0%
i36
25.0%
m36
25.0%
N18
12.5%
o18
12.5%
None
ValueCountFrequency (%)
ã18
100.0%

usotox
Categorical

HIGH CORRELATION
MISSING

Distinct14
Distinct (%)25.9%
Missing3
Missing (%)5.3%
Memory size584.0 B
Maconha
20 
Nunca utilizei nenhuma dessas substâncias
14 
Maconha Cocaína
Maconha LSD
 
2
Maconha Cocaína Crack
 
1
Other values (9)

Length

Max length46
Median length43
Mean length21.07407407
Min length7

Characters and Unicode

Total characters1138
Distinct characters38
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)18.5%

Sample

1st rowMaconha
2nd rowMaconha
3rd rowMaconha
4th rowNunca utilizei nenhuma dessas substâncias
5th rowNunca utilizei nenhuma dessas substâncias

Common Values

ValueCountFrequency (%)
Maconha20
35.1%
Nunca utilizei nenhuma dessas substâncias14
24.6%
Maconha Cocaína8
 
14.0%
Maconha LSD2
 
3.5%
Maconha Cocaína Crack1
 
1.8%
Maconha Bala1
 
1.8%
Maconha Cocaína LSD Outras1
 
1.8%
Maconha LSD Skank, Tubo de lança, Special K1
 
1.8%
Maconha Cocaína LSD Loló, Lança Perfume1
 
1.8%
Maconha Cocaína Crack lolo´, bala, black lança1
 
1.8%
Other values (4)4
 
7.0%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:43.308072image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
maconha40
25.8%
cocaína15
 
9.7%
nunca14
 
9.0%
utilizei14
 
9.0%
nenhuma14
 
9.0%
dessas14
 
9.0%
substâncias14
 
9.0%
lsd8
 
5.2%
crack4
 
2.6%
lança3
 
1.9%
Other values (13)15
 
9.7%

Most occurring characters

ValueCountFrequency (%)
a186
16.3%
n115
10.1%
101
 
8.9%
c89
 
7.8%
s88
 
7.7%
o61
 
5.4%
u60
 
5.3%
i57
 
5.0%
h54
 
4.7%
e47
 
4.1%
Other values (28)280
24.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter922
81.0%
Uppercase Letter109
 
9.6%
Space Separator101
 
8.9%
Other Punctuation5
 
0.4%
Modifier Symbol1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a186
20.2%
n115
12.5%
c89
9.7%
s88
9.5%
o61
 
6.6%
u60
 
6.5%
i57
 
6.2%
h54
 
5.9%
e47
 
5.1%
t31
 
3.4%
Other values (13)134
14.5%
Uppercase Letter
ValueCountFrequency (%)
M40
36.7%
C19
17.4%
N14
 
12.8%
L11
 
10.1%
S10
 
9.2%
D8
 
7.3%
O2
 
1.8%
P1
 
0.9%
B1
 
0.9%
K1
 
0.9%
Other values (2)2
 
1.8%
Space Separator
ValueCountFrequency (%)
101
100.0%
Other Punctuation
ValueCountFrequency (%)
,5
100.0%
Modifier Symbol
ValueCountFrequency (%)
´1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1031
90.6%
Common107
 
9.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a186
18.0%
n115
11.2%
c89
 
8.6%
s88
 
8.5%
o61
 
5.9%
u60
 
5.8%
i57
 
5.5%
h54
 
5.2%
e47
 
4.6%
M40
 
3.9%
Other values (25)234
22.7%
Common
ValueCountFrequency (%)
101
94.4%
,5
 
4.7%
´1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII1104
97.0%
None34
 
3.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a186
16.8%
n115
10.4%
101
9.1%
c89
 
8.1%
s88
 
8.0%
o61
 
5.5%
u60
 
5.4%
i57
 
5.2%
h54
 
4.9%
e47
 
4.3%
Other values (23)246
22.3%
None
ValueCountFrequency (%)
í15
44.1%
â14
41.2%
ç3
 
8.8%
ó1
 
2.9%
´1
 
2.9%

motnfrequs
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)26.7%
Missing42
Missing (%)73.7%
Memory size584.0 B
O serviço é limitado
Prefiro me consultar em outros lugares
Vergonha
Sofri(o) discriminação

Length

Max length38
Median length22
Mean length24.53333333
Min length8

Characters and Unicode

Total characters368
Distinct characters27
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)6.7%

Sample

1st rowO serviço é limitado
2nd rowPrefiro me consultar em outros lugares
3rd rowPrefiro me consultar em outros lugares
4th rowVergonha
5th rowO serviço é limitado

Common Values

ValueCountFrequency (%)
O serviço é limitado7
 
12.3%
Prefiro me consultar em outros lugares5
 
8.8%
Vergonha2
 
3.5%
Sofri(o) discriminação1
 
1.8%
(Missing)42
73.7%

Length

2022-05-31T15:05:43.478658image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:43.613296image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
o7
11.3%
serviço7
11.3%
é7
11.3%
limitado7
11.3%
prefiro5
8.1%
me5
8.1%
consultar5
8.1%
em5
8.1%
outros5
8.1%
lugares5
8.1%
Other values (3)4
6.5%

Most occurring characters

ValueCountFrequency (%)
47
12.8%
o39
10.6%
r36
 
9.8%
i30
 
8.2%
e29
 
7.9%
s23
 
6.2%
a20
 
5.4%
m18
 
4.9%
l17
 
4.6%
t17
 
4.6%
Other values (17)92
25.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter304
82.6%
Space Separator47
 
12.8%
Uppercase Letter15
 
4.1%
Open Punctuation1
 
0.3%
Close Punctuation1
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o39
12.8%
r36
11.8%
i30
9.9%
e29
9.5%
s23
 
7.6%
a20
 
6.6%
m18
 
5.9%
l17
 
5.6%
t17
 
5.6%
u15
 
4.9%
Other values (10)60
19.7%
Uppercase Letter
ValueCountFrequency (%)
O7
46.7%
P5
33.3%
V2
 
13.3%
S1
 
6.7%
Space Separator
ValueCountFrequency (%)
47
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin319
86.7%
Common49
 
13.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o39
12.2%
r36
11.3%
i30
 
9.4%
e29
 
9.1%
s23
 
7.2%
a20
 
6.3%
m18
 
5.6%
l17
 
5.3%
t17
 
5.3%
u15
 
4.7%
Other values (14)75
23.5%
Common
ValueCountFrequency (%)
47
95.9%
(1
 
2.0%
)1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII352
95.7%
None16
 
4.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
47
13.4%
o39
11.1%
r36
10.2%
i30
 
8.5%
e29
 
8.2%
s23
 
6.5%
a20
 
5.7%
m18
 
5.1%
l17
 
4.8%
t17
 
4.8%
Other values (14)76
21.6%
None
ValueCountFrequency (%)
ç8
50.0%
é7
43.8%
ã1
 
6.2%

assistpsi
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)7.4%
Missing3
Missing (%)5.3%
Memory size584.0 B
Não
25 
Sim, e frequento(ei) por vontade própria
22 
Tenho a possibilidade de frequentar mas nunca fui
Sim, mas fui obrigada
 
1

Length

Max length49
Median length40
Mean length23.51851852
Min length3

Characters and Unicode

Total characters1270
Distinct characters29
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st rowSim, e frequento(ei) por vontade própria
2nd rowNão
3rd rowNão
4th rowNão
5th rowNão

Common Values

ValueCountFrequency (%)
Não25
43.9%
Sim, e frequento(ei) por vontade própria22
38.6%
Tenho a possibilidade de frequentar mas nunca fui6
 
10.5%
Sim, mas fui obrigada1
 
1.8%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:43.746189image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:43.861880image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não25
12.0%
sim23
11.0%
e22
10.5%
frequento(ei22
10.5%
por22
10.5%
vontade22
10.5%
própria22
10.5%
mas7
 
3.3%
fui7
 
3.3%
tenho6
 
2.9%
Other values (6)31
14.8%

Most occurring characters

ValueCountFrequency (%)
155
12.2%
e140
 
11.0%
o104
 
8.2%
r101
 
8.0%
i93
 
7.3%
a77
 
6.1%
p72
 
5.7%
n68
 
5.4%
t50
 
3.9%
d41
 
3.2%
Other values (19)369
29.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter994
78.3%
Space Separator155
 
12.2%
Uppercase Letter54
 
4.3%
Other Punctuation23
 
1.8%
Open Punctuation22
 
1.7%
Close Punctuation22
 
1.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e140
14.1%
o104
10.5%
r101
10.2%
i93
9.4%
a77
 
7.7%
p72
 
7.2%
n68
 
6.8%
t50
 
5.0%
d41
 
4.1%
u41
 
4.1%
Other values (12)207
20.8%
Uppercase Letter
ValueCountFrequency (%)
N25
46.3%
S23
42.6%
T6
 
11.1%
Space Separator
ValueCountFrequency (%)
155
100.0%
Other Punctuation
ValueCountFrequency (%)
,23
100.0%
Open Punctuation
ValueCountFrequency (%)
(22
100.0%
Close Punctuation
ValueCountFrequency (%)
)22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1048
82.5%
Common222
 
17.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e140
13.4%
o104
 
9.9%
r101
 
9.6%
i93
 
8.9%
a77
 
7.3%
p72
 
6.9%
n68
 
6.5%
t50
 
4.8%
d41
 
3.9%
u41
 
3.9%
Other values (15)261
24.9%
Common
ValueCountFrequency (%)
155
69.8%
,23
 
10.4%
(22
 
9.9%
)22
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII1223
96.3%
None47
 
3.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
155
12.7%
e140
11.4%
o104
 
8.5%
r101
 
8.3%
i93
 
7.6%
a77
 
6.3%
p72
 
5.9%
n68
 
5.6%
t50
 
4.1%
d41
 
3.4%
Other values (17)322
26.3%
None
ValueCountFrequency (%)
ã25
53.2%
ó22
46.8%

servpsi
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)5.6%
Missing3
Missing (%)5.3%
Memory size584.0 B
Não sei
20 
Não
18 
Sim
16 

Length

Max length7
Median length3
Mean length4.481481481
Min length3

Characters and Unicode

Total characters242
Distinct characters9
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowNão sei
3rd rowNão sei
4th rowSim
5th rowSim

Common Values

ValueCountFrequency (%)
Não sei20
35.1%
Não18
31.6%
Sim16
28.1%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:43.998516image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:44.132157image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não38
51.4%
sei20
27.0%
sim16
21.6%

Most occurring characters

ValueCountFrequency (%)
N38
15.7%
ã38
15.7%
o38
15.7%
i36
14.9%
20
8.3%
s20
8.3%
e20
8.3%
S16
6.6%
m16
6.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter168
69.4%
Uppercase Letter54
 
22.3%
Space Separator20
 
8.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
ã38
22.6%
o38
22.6%
i36
21.4%
s20
11.9%
e20
11.9%
m16
9.5%
Uppercase Letter
ValueCountFrequency (%)
N38
70.4%
S16
29.6%
Space Separator
ValueCountFrequency (%)
20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin222
91.7%
Common20
 
8.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
N38
17.1%
ã38
17.1%
o38
17.1%
i36
16.2%
s20
9.0%
e20
9.0%
S16
7.2%
m16
7.2%
Common
ValueCountFrequency (%)
20
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII204
84.3%
None38
 
15.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N38
18.6%
o38
18.6%
i36
17.6%
20
9.8%
s20
9.8%
e20
9.8%
S16
7.8%
m16
7.8%
None
ValueCountFrequency (%)
ã38
100.0%

servsoc
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)5.6%
Missing3
Missing (%)5.3%
Memory size584.0 B
Sim
22 
Não sei
18 
Não
14 

Length

Max length7
Median length3
Mean length4.333333333
Min length3

Characters and Unicode

Total characters234
Distinct characters9
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowNão sei
3rd rowNão sei
4th rowSim
5th rowNão sei

Common Values

ValueCountFrequency (%)
Sim22
38.6%
Não sei18
31.6%
Não14
24.6%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:44.246852image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:44.371516image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não32
44.4%
sim22
30.6%
sei18
25.0%

Most occurring characters

ValueCountFrequency (%)
i40
17.1%
N32
13.7%
ã32
13.7%
o32
13.7%
S22
9.4%
m22
9.4%
18
7.7%
s18
7.7%
e18
7.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter162
69.2%
Uppercase Letter54
 
23.1%
Space Separator18
 
7.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i40
24.7%
ã32
19.8%
o32
19.8%
m22
13.6%
s18
11.1%
e18
11.1%
Uppercase Letter
ValueCountFrequency (%)
N32
59.3%
S22
40.7%
Space Separator
ValueCountFrequency (%)
18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin216
92.3%
Common18
 
7.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
i40
18.5%
N32
14.8%
ã32
14.8%
o32
14.8%
S22
10.2%
m22
10.2%
s18
8.3%
e18
8.3%
Common
ValueCountFrequency (%)
18
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII202
86.3%
None32
 
13.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i40
19.8%
N32
15.8%
o32
15.8%
S22
10.9%
m22
10.9%
18
8.9%
s18
8.9%
e18
8.9%
None
ValueCountFrequency (%)
ã32
100.0%

medcserv
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)7.4%
Missing3
Missing (%)5.3%
Memory size584.0 B
Sim, mas o serviço é ruim, quase nunca tem medicamentos
17 
Sim, e o serviço é bom
16 
Não
12 
Não sei

Length

Max length55
Median length22
Mean length25.66666667
Min length3

Characters and Unicode

Total characters1386
Distinct characters22
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim, mas o serviço é ruim, quase nunca tem medicamentos
2nd rowNão sei
3rd rowSim, mas o serviço é ruim, quase nunca tem medicamentos
4th rowSim, e o serviço é bom
5th rowSim, mas o serviço é ruim, quase nunca tem medicamentos

Common Values

ValueCountFrequency (%)
Sim, mas o serviço é ruim, quase nunca tem medicamentos17
29.8%
Sim, e o serviço é bom16
28.1%
Não12
21.1%
Não sei9
15.8%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:44.476236image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:44.605891image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim33
11.1%
o33
11.1%
serviço33
11.1%
é33
11.1%
não21
 
7.1%
mas17
 
5.7%
ruim17
 
5.7%
quase17
 
5.7%
nunca17
 
5.7%
tem17
 
5.7%
Other values (4)58
19.6%

Most occurring characters

ValueCountFrequency (%)
242
17.5%
m134
 
9.7%
e126
 
9.1%
o120
 
8.7%
i109
 
7.9%
s93
 
6.7%
a68
 
4.9%
n51
 
3.7%
u51
 
3.7%
,50
 
3.6%
Other values (12)342
24.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1040
75.0%
Space Separator242
 
17.5%
Uppercase Letter54
 
3.9%
Other Punctuation50
 
3.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
m134
12.9%
e126
12.1%
o120
11.5%
i109
10.5%
s93
8.9%
a68
 
6.5%
n51
 
4.9%
u51
 
4.9%
r50
 
4.8%
t34
 
3.3%
Other values (8)204
19.6%
Uppercase Letter
ValueCountFrequency (%)
S33
61.1%
N21
38.9%
Space Separator
ValueCountFrequency (%)
242
100.0%
Other Punctuation
ValueCountFrequency (%)
,50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1094
78.9%
Common292
 
21.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
m134
12.2%
e126
11.5%
o120
11.0%
i109
10.0%
s93
 
8.5%
a68
 
6.2%
n51
 
4.7%
u51
 
4.7%
r50
 
4.6%
t34
 
3.1%
Other values (10)258
23.6%
Common
ValueCountFrequency (%)
242
82.9%
,50
 
17.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII1299
93.7%
None87
 
6.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
242
18.6%
m134
10.3%
e126
9.7%
o120
9.2%
i109
8.4%
s93
 
7.2%
a68
 
5.2%
n51
 
3.9%
u51
 
3.9%
,50
 
3.8%
Other values (9)255
19.6%
None
ValueCountFrequency (%)
ç33
37.9%
é33
37.9%
ã21
24.1%

vaccovid
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)5.7%
Missing4
Missing (%)7.0%
Memory size584.0 B
Sim, e já estou imunizada
50 
Sim, mas ainda falta tomar a segunda dose
 
2
Ainda não, mas quero me vacinar
 
1

Length

Max length41
Median length25
Mean length25.71698113
Min length25

Characters and Unicode

Total characters1363
Distinct characters25
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st rowSim, e já estou imunizada
2nd rowSim, e já estou imunizada
3rd rowSim, e já estou imunizada
4th rowSim, e já estou imunizada
5th rowSim, e já estou imunizada

Common Values

ValueCountFrequency (%)
Sim, e já estou imunizada50
87.7%
Sim, mas ainda falta tomar a segunda dose2
 
3.5%
Ainda não, mas quero me vacinar1
 
1.8%
(Missing)4
 
7.0%

Length

2022-05-31T15:05:44.734546image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:44.854395image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim52
19.1%
e50
18.4%
50
18.4%
estou50
18.4%
imunizada50
18.4%
mas3
 
1.1%
ainda3
 
1.1%
falta2
 
0.7%
tomar2
 
0.7%
a2
 
0.7%
Other values (6)8
 
2.9%

Most occurring characters

ValueCountFrequency (%)
219
16.1%
i156
11.4%
a120
 
8.8%
m108
 
7.9%
e106
 
7.8%
u103
 
7.6%
n57
 
4.2%
d57
 
4.2%
s57
 
4.2%
o56
 
4.1%
Other values (15)324
23.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1038
76.2%
Space Separator219
 
16.1%
Other Punctuation53
 
3.9%
Uppercase Letter53
 
3.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i156
15.0%
a120
11.6%
m108
10.4%
e106
10.2%
u103
9.9%
n57
 
5.5%
d57
 
5.5%
s57
 
5.5%
o56
 
5.4%
t54
 
5.2%
Other values (11)164
15.8%
Uppercase Letter
ValueCountFrequency (%)
S52
98.1%
A1
 
1.9%
Space Separator
ValueCountFrequency (%)
219
100.0%
Other Punctuation
ValueCountFrequency (%)
,53
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1091
80.0%
Common272
 
20.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i156
14.3%
a120
11.0%
m108
9.9%
e106
9.7%
u103
9.4%
n57
 
5.2%
d57
 
5.2%
s57
 
5.2%
o56
 
5.1%
t54
 
4.9%
Other values (13)217
19.9%
Common
ValueCountFrequency (%)
219
80.5%
,53
 
19.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII1312
96.3%
None51
 
3.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
219
16.7%
i156
11.9%
a120
9.1%
m108
 
8.2%
e106
 
8.1%
u103
 
7.9%
n57
 
4.3%
d57
 
4.3%
s57
 
4.3%
o56
 
4.3%
Other values (13)273
20.8%
None
ValueCountFrequency (%)
á50
98.0%
ã1
 
2.0%

vacvida
Categorical

HIGH CORRELATION
MISSING

Distinct39
Distinct (%)72.2%
Missing3
Missing (%)5.3%
Memory size584.0 B
Não sei/ não lembro
10 
Hepatite B e C Gripe Sarampo Poliomielite Febre Amarela Tríplice Viral BCG-Turberculose HPV Pneumocócica Dupla-Tétano Triplice Bacteriana-dTpa
 
3
Gripe
 
2
Hepatite B e C Gripe Sarampo Poliomielite Febre Amarela Tríplice Viral BCG-Turberculose HPV
 
2
Hepatite B e C Gripe Sarampo Poliomielite Febre Amarela Tríplice Viral BCG-Turberculose Pneumocócica Dupla-Tétano Triplice Bacteriana-dTpa
 
2
Other values (34)
35 

Length

Max length150
Median length113
Mean length75.55555556
Min length5

Characters and Unicode

Total characters4080
Distinct characters36
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)61.1%

Sample

1st rowGripe Sarampo Febre Amarela Tríplice Viral Sífilis HPV Não sei/ não lembro
2nd rowNão sei/ não lembro
3rd rowNão sei/ não lembro
4th rowNão sei/ não lembro
5th rowNão sei/ não lembro

Common Values

ValueCountFrequency (%)
Não sei/ não lembro10
 
17.5%
Hepatite B e C Gripe Sarampo Poliomielite Febre Amarela Tríplice Viral BCG-Turberculose HPV Pneumocócica Dupla-Tétano Triplice Bacteriana-dTpa3
 
5.3%
Gripe2
 
3.5%
Hepatite B e C Gripe Sarampo Poliomielite Febre Amarela Tríplice Viral BCG-Turberculose HPV2
 
3.5%
Hepatite B e C Gripe Sarampo Poliomielite Febre Amarela Tríplice Viral BCG-Turberculose Pneumocócica Dupla-Tétano Triplice Bacteriana-dTpa2
 
3.5%
Hepatite B e C Gripe Sarampo Poliomielite Febre Amarela Tríplice Viral HPV Dupla-Tétano Triplice Bacteriana-dTpa Não sei/ não lembro2
 
3.5%
Hepatite B e C Gripe Sarampo Febre Amarela Sífilis HPV1
 
1.8%
Gripe BCG-Turberculose HPV Não lembra ou não sabe se tomou as vacinas acima1
 
1.8%
Gripe Sarampo Febre Amarela BCG-Turberculose Dupla-Tétano Não sei/ não lembro1
 
1.8%
Hepatite B e C Gripe Sarampo Febre Amarela Tríplice Viral BCG-Turberculose Sífilis1
 
1.8%
Other values (29)29
50.9%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:45.766350image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
não48
 
8.4%
gripe36
 
6.3%
sarampo34
 
6.0%
hepatite33
 
5.8%
b33
 
5.8%
e33
 
5.8%
c33
 
5.8%
febre30
 
5.3%
amarela30
 
5.3%
tríplice27
 
4.7%
Other values (19)232
40.8%

Most occurring characters

ValueCountFrequency (%)
515
 
12.6%
e445
 
10.9%
a325
 
8.0%
i303
 
7.4%
r290
 
7.1%
l236
 
5.8%
o222
 
5.4%
p189
 
4.6%
t135
 
3.3%
m127
 
3.1%
Other values (26)1293
31.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2858
70.0%
Uppercase Letter616
 
15.1%
Space Separator515
 
12.6%
Dash Punctuation68
 
1.7%
Other Punctuation23
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e445
15.6%
a325
11.4%
i303
10.6%
r290
10.1%
l236
8.3%
o222
7.8%
p189
6.6%
t135
 
4.7%
m127
 
4.4%
c122
 
4.3%
Other values (11)464
16.2%
Uppercase Letter
ValueCountFrequency (%)
T111
18.0%
B74
12.0%
G61
9.9%
C58
9.4%
P57
9.3%
H53
8.6%
V47
7.6%
S44
 
7.1%
F30
 
4.9%
A30
 
4.9%
Other values (2)51
8.3%
Space Separator
ValueCountFrequency (%)
515
100.0%
Dash Punctuation
ValueCountFrequency (%)
-68
100.0%
Other Punctuation
ValueCountFrequency (%)
/23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3474
85.1%
Common606
 
14.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e445
12.8%
a325
 
9.4%
i303
 
8.7%
r290
 
8.3%
l236
 
6.8%
o222
 
6.4%
p189
 
5.4%
t135
 
3.9%
m127
 
3.7%
c122
 
3.5%
Other values (23)1080
31.1%
Common
ValueCountFrequency (%)
515
85.0%
-68
 
11.2%
/23
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII3956
97.0%
None124
 
3.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
515
13.0%
e445
 
11.2%
a325
 
8.2%
i303
 
7.7%
r290
 
7.3%
l236
 
6.0%
o222
 
5.6%
p189
 
4.8%
t135
 
3.4%
m127
 
3.2%
Other values (22)1169
29.6%
None
ValueCountFrequency (%)
ã48
38.7%
í37
29.8%
é27
21.8%
ó12
 
9.7%

plansaude
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)5.7%
Missing4
Missing (%)7.0%
Memory size584.0 B
Não possuo
49 
Sim, através da empresa onde trabalho
 
2
Sim, sou dependente do plano de saúde de outra pessoa
 
2

Length

Max length53
Median length10
Mean length12.64150943
Min length10

Characters and Unicode

Total characters670
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão possuo
2nd rowNão possuo
3rd rowNão possuo
4th rowNão possuo
5th rowNão possuo

Common Values

ValueCountFrequency (%)
Não possuo49
86.0%
Sim, através da empresa onde trabalho2
 
3.5%
Sim, sou dependente do plano de saúde de outra pessoa2
 
3.5%
(Missing)4
 
7.0%

Length

2022-05-31T15:05:45.894970image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:46.013652image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não49
37.7%
possuo49
37.7%
sim4
 
3.1%
de4
 
3.1%
através2
 
1.5%
da2
 
1.5%
empresa2
 
1.5%
onde2
 
1.5%
trabalho2
 
1.5%
sou2
 
1.5%
Other values (6)12
 
9.2%

Most occurring characters

ValueCountFrequency (%)
o161
24.0%
s110
16.4%
77
11.5%
p57
 
8.5%
u53
 
7.9%
N49
 
7.3%
ã49
 
7.3%
e22
 
3.3%
a20
 
3.0%
d16
 
2.4%
Other values (13)56
 
8.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter536
80.0%
Space Separator77
 
11.5%
Uppercase Letter53
 
7.9%
Other Punctuation4
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o161
30.0%
s110
20.5%
p57
 
10.6%
u53
 
9.9%
ã49
 
9.1%
e22
 
4.1%
a20
 
3.7%
d16
 
3.0%
t8
 
1.5%
r8
 
1.5%
Other values (9)32
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
N49
92.5%
S4
 
7.5%
Space Separator
ValueCountFrequency (%)
77
100.0%
Other Punctuation
ValueCountFrequency (%)
,4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin589
87.9%
Common81
 
12.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o161
27.3%
s110
18.7%
p57
 
9.7%
u53
 
9.0%
N49
 
8.3%
ã49
 
8.3%
e22
 
3.7%
a20
 
3.4%
d16
 
2.7%
t8
 
1.4%
Other values (11)44
 
7.5%
Common
ValueCountFrequency (%)
77
95.1%
,4
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII617
92.1%
None53
 
7.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o161
26.1%
s110
17.8%
77
12.5%
p57
 
9.2%
u53
 
8.6%
N49
 
7.9%
e22
 
3.6%
a20
 
3.2%
d16
 
2.6%
t8
 
1.3%
Other values (10)44
 
7.1%
None
ValueCountFrequency (%)
ã49
92.5%
é2
 
3.8%
ú2
 
3.8%

disttranst
Categorical

HIGH CORRELATION
MISSING

Distinct6
Distinct (%)11.1%
Missing3
Missing (%)5.3%
Memory size584.0 B
Não possuo nenhum diagnóstico
26 
Sim, com laudo psiquiátrico
Não sei
Sim, mas não possuo laudo
Não, mas tenho autodiagnostico ou suspeita

Length

Max length42
Median length29
Mean length27.07407407
Min length7

Characters and Unicode

Total characters1462
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st rowNão sei
2nd rowNão sei
3rd rowNão possuo nenhum diagnóstico
4th rowNão possuo nenhum diagnóstico
5th rowNão possuo nenhum diagnóstico

Common Values

ValueCountFrequency (%)
Não possuo nenhum diagnóstico26
45.6%
Sim, com laudo psiquiátrico9
 
15.8%
Não sei6
 
10.5%
Sim, mas não possuo laudo6
 
10.5%
Não, mas tenho autodiagnostico ou suspeita6
 
10.5%
Prefiro não responder1
 
1.8%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:46.144302image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:46.285961image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não45
20.4%
possuo32
14.5%
nenhum26
11.8%
diagnóstico26
11.8%
sim15
 
6.8%
laudo15
 
6.8%
mas12
 
5.4%
com9
 
4.1%
psiquiátrico9
 
4.1%
sei6
 
2.7%
Other values (6)26
11.8%

Most occurring characters

ValueCountFrequency (%)
o200
13.7%
167
11.4%
s136
 
9.3%
i119
 
8.1%
u100
 
6.8%
n98
 
6.7%
a71
 
4.9%
m62
 
4.2%
t59
 
4.0%
c50
 
3.4%
Other values (16)400
27.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1220
83.4%
Space Separator167
 
11.4%
Uppercase Letter54
 
3.7%
Other Punctuation21
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o200
16.4%
s136
11.1%
i119
9.8%
u100
 
8.2%
n98
 
8.0%
a71
 
5.8%
m62
 
5.1%
t59
 
4.8%
c50
 
4.1%
p48
 
3.9%
Other values (11)277
22.7%
Uppercase Letter
ValueCountFrequency (%)
N38
70.4%
S15
 
27.8%
P1
 
1.9%
Space Separator
ValueCountFrequency (%)
167
100.0%
Other Punctuation
ValueCountFrequency (%)
,21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1274
87.1%
Common188
 
12.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o200
15.7%
s136
10.7%
i119
 
9.3%
u100
 
7.8%
n98
 
7.7%
a71
 
5.6%
m62
 
4.9%
t59
 
4.6%
c50
 
3.9%
p48
 
3.8%
Other values (14)331
26.0%
Common
ValueCountFrequency (%)
167
88.8%
,21
 
11.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII1382
94.5%
None80
 
5.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o200
14.5%
167
12.1%
s136
9.8%
i119
 
8.6%
u100
 
7.2%
n98
 
7.1%
a71
 
5.1%
m62
 
4.5%
t59
 
4.3%
c50
 
3.6%
Other values (13)320
23.2%
None
ValueCountFrequency (%)
ã45
56.2%
ó26
32.5%
á9
 
11.2%

alimen
Categorical

HIGH CORRELATION
MISSING

Distinct5
Distinct (%)9.3%
Missing3
Missing (%)5.3%
Memory size584.0 B
Sim, três ou mais vezes ao dia
33 
Sim, pelo menos duas vezes ao dia
14 
Sim, uma vez ao dia
Tenho dificuldade em me alimentar regularmente
 
2
Dia sim, dia não
 
1

Length

Max length46
Median length30
Mean length30.2962963
Min length16

Characters and Unicode

Total characters1636
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st rowSim, pelo menos duas vezes ao dia
2nd rowSim, pelo menos duas vezes ao dia
3rd rowSim, três ou mais vezes ao dia
4th rowSim, pelo menos duas vezes ao dia
5th rowSim, três ou mais vezes ao dia

Common Values

ValueCountFrequency (%)
Sim, três ou mais vezes ao dia33
57.9%
Sim, pelo menos duas vezes ao dia14
24.6%
Sim, uma vez ao dia4
 
7.0%
Tenho dificuldade em me alimentar regularmente2
 
3.5%
Dia sim, dia não1
 
1.8%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:46.430535image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:46.561230image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
dia53
14.5%
sim52
14.2%
ao51
14.0%
vezes47
12.9%
ou33
9.0%
mais33
9.0%
três33
9.0%
menos14
 
3.8%
duas14
 
3.8%
pelo14
 
3.8%
Other values (9)21
 
5.8%

Most occurring characters

ValueCountFrequency (%)
311
19.0%
a163
10.0%
i144
8.8%
e142
8.7%
s142
8.7%
o115
 
7.0%
m111
 
6.8%
d72
 
4.4%
u55
 
3.4%
,52
 
3.2%
Other values (16)329
20.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1219
74.5%
Space Separator311
 
19.0%
Uppercase Letter54
 
3.3%
Other Punctuation52
 
3.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a163
13.4%
i144
11.8%
e142
11.6%
s142
11.6%
o115
9.4%
m111
9.1%
d72
5.9%
u55
 
4.5%
v51
 
4.2%
z51
 
4.2%
Other values (11)173
14.2%
Uppercase Letter
ValueCountFrequency (%)
S51
94.4%
T2
 
3.7%
D1
 
1.9%
Space Separator
ValueCountFrequency (%)
311
100.0%
Other Punctuation
ValueCountFrequency (%)
,52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1273
77.8%
Common363
 
22.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a163
12.8%
i144
11.3%
e142
11.2%
s142
11.2%
o115
9.0%
m111
8.7%
d72
 
5.7%
u55
 
4.3%
v51
 
4.0%
z51
 
4.0%
Other values (14)227
17.8%
Common
ValueCountFrequency (%)
311
85.7%
,52
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII1602
97.9%
None34
 
2.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
311
19.4%
a163
10.2%
i144
9.0%
e142
8.9%
s142
8.9%
o115
 
7.2%
m111
 
6.9%
d72
 
4.5%
u55
 
3.4%
,52
 
3.2%
Other values (14)295
18.4%
None
ValueCountFrequency (%)
ê33
97.1%
ã1
 
2.9%

expohiv
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)5.9%
Missing6
Missing (%)10.5%
Memory size584.0 B
Não sei
43 
Sim, uma vez
Sim, inúmeras vezes
 
1

Length

Max length19
Median length7
Mean length7.921568627
Min length7

Characters and Unicode

Total characters404
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)2.0%

Sample

1st rowSim, uma vez
2nd rowSim, inúmeras vezes
3rd rowNão sei
4th rowNão sei
5th rowNão sei

Common Values

ValueCountFrequency (%)
Não sei43
75.4%
Sim, uma vez7
 
12.3%
Sim, inúmeras vezes1
 
1.8%
(Missing)6
 
10.5%

Length

2022-05-31T15:05:46.688889image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:46.809561image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não43
39.1%
sei43
39.1%
sim8
 
7.3%
uma7
 
6.4%
vez7
 
6.4%
inúmeras1
 
0.9%
vezes1
 
0.9%

Most occurring characters

ValueCountFrequency (%)
59
14.6%
e53
13.1%
i52
12.9%
s45
11.1%
N43
10.6%
ã43
10.6%
o43
10.6%
m16
 
4.0%
S8
 
2.0%
,8
 
2.0%
Other values (7)34
8.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter286
70.8%
Space Separator59
 
14.6%
Uppercase Letter51
 
12.6%
Other Punctuation8
 
2.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e53
18.5%
i52
18.2%
s45
15.7%
ã43
15.0%
o43
15.0%
m16
 
5.6%
a8
 
2.8%
v8
 
2.8%
z8
 
2.8%
u7
 
2.4%
Other values (3)3
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
N43
84.3%
S8
 
15.7%
Space Separator
ValueCountFrequency (%)
59
100.0%
Other Punctuation
ValueCountFrequency (%)
,8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin337
83.4%
Common67
 
16.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e53
15.7%
i52
15.4%
s45
13.4%
N43
12.8%
ã43
12.8%
o43
12.8%
m16
 
4.7%
S8
 
2.4%
a8
 
2.4%
v8
 
2.4%
Other values (5)18
 
5.3%
Common
ValueCountFrequency (%)
59
88.1%
,8
 
11.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII360
89.1%
None44
 
10.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
59
16.4%
e53
14.7%
i52
14.4%
s45
12.5%
N43
11.9%
o43
11.9%
m16
 
4.4%
S8
 
2.2%
,8
 
2.2%
a8
 
2.2%
Other values (5)25
6.9%
None
ValueCountFrequency (%)
ã43
97.7%
ú1
 
2.3%

servcsf
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)5.6%
Missing3
Missing (%)5.3%
Memory size584.0 B
Não utilizo
24 
Sim, ocasionalmente
18 
Sim, regularmente
12 

Length

Max length19
Median length17
Mean length15
Min length11

Characters and Unicode

Total characters810
Distinct characters19
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão utilizo
2nd rowNão utilizo
3rd rowSim, ocasionalmente
4th rowSim, regularmente
5th rowSim, ocasionalmente

Common Values

ValueCountFrequency (%)
Não utilizo24
42.1%
Sim, ocasionalmente18
31.6%
Sim, regularmente12
21.1%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:46.924595image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:47.047309image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim30
27.8%
não24
22.2%
utilizo24
22.2%
ocasionalmente18
16.7%
regularmente12
 
11.1%

Most occurring characters

ValueCountFrequency (%)
i96
11.9%
o84
10.4%
e72
 
8.9%
m60
 
7.4%
54
 
6.7%
t54
 
6.7%
l54
 
6.7%
a48
 
5.9%
n48
 
5.9%
u36
 
4.4%
Other values (9)204
25.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter672
83.0%
Space Separator54
 
6.7%
Uppercase Letter54
 
6.7%
Other Punctuation30
 
3.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i96
14.3%
o84
12.5%
e72
10.7%
m60
8.9%
t54
8.0%
l54
8.0%
a48
7.1%
n48
7.1%
u36
 
5.4%
r24
 
3.6%
Other values (5)96
14.3%
Uppercase Letter
ValueCountFrequency (%)
S30
55.6%
N24
44.4%
Space Separator
ValueCountFrequency (%)
54
100.0%
Other Punctuation
ValueCountFrequency (%)
,30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin726
89.6%
Common84
 
10.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
i96
13.2%
o84
11.6%
e72
9.9%
m60
8.3%
t54
 
7.4%
l54
 
7.4%
a48
 
6.6%
n48
 
6.6%
u36
 
5.0%
S30
 
4.1%
Other values (7)144
19.8%
Common
ValueCountFrequency (%)
54
64.3%
,30
35.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII786
97.0%
None24
 
3.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i96
12.2%
o84
10.7%
e72
 
9.2%
m60
 
7.6%
54
 
6.9%
t54
 
6.9%
l54
 
6.9%
a48
 
6.1%
n48
 
6.1%
u36
 
4.6%
Other values (8)180
22.9%
None
ValueCountFrequency (%)
ã24
100.0%

naocsf
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)19.0%
Missing36
Missing (%)63.2%
Memory size584.0 B
Os serviços são ruins
12 
Não consegui realizar meu cadastro
Já fui maltratada/desrespeitada
Tenho vergonha de expor minha situação de saúde no bairro/comunidade
 
1

Length

Max length68
Median length21
Mean length27.9047619
Min length21

Characters and Unicode

Total characters586
Distinct characters31
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)4.8%

Sample

1st rowNão consegui realizar meu cadastro
2nd rowOs serviços são ruins
3rd rowOs serviços são ruins
4th rowOs serviços são ruins
5th rowNão consegui realizar meu cadastro

Common Values

ValueCountFrequency (%)
Os serviços são ruins12
 
21.1%
Não consegui realizar meu cadastro6
 
10.5%
Já fui maltratada/desrespeitada2
 
3.5%
Tenho vergonha de expor minha situação de saúde no bairro/comunidade1
 
1.8%
(Missing)36
63.2%

Length

2022-05-31T15:05:47.165950image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:47.338487image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
os12
12.8%
são12
12.8%
ruins12
12.8%
serviços12
12.8%
não6
6.4%
consegui6
6.4%
realizar6
6.4%
meu6
6.4%
cadastro6
6.4%
maltratada/desrespeitada2
 
2.1%
Other values (11)14
14.9%

Most occurring characters

ValueCountFrequency (%)
s78
13.3%
73
12.5%
r50
 
8.5%
o49
 
8.4%
i44
 
7.5%
e43
 
7.3%
a42
 
7.2%
u28
 
4.8%
n23
 
3.9%
ã19
 
3.2%
Other values (21)137
23.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter489
83.4%
Space Separator73
 
12.5%
Uppercase Letter21
 
3.6%
Other Punctuation3
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s78
16.0%
r50
10.2%
o49
10.0%
i44
9.0%
e43
8.8%
a42
8.6%
u28
 
5.7%
n23
 
4.7%
ã19
 
3.9%
d17
 
3.5%
Other values (15)96
19.6%
Uppercase Letter
ValueCountFrequency (%)
O12
57.1%
N6
28.6%
J2
 
9.5%
T1
 
4.8%
Space Separator
ValueCountFrequency (%)
73
100.0%
Other Punctuation
ValueCountFrequency (%)
/3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin510
87.0%
Common76
 
13.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
s78
15.3%
r50
9.8%
o49
9.6%
i44
 
8.6%
e43
 
8.4%
a42
 
8.2%
u28
 
5.5%
n23
 
4.5%
ã19
 
3.7%
d17
 
3.3%
Other values (19)117
22.9%
Common
ValueCountFrequency (%)
73
96.1%
/3
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII551
94.0%
None35
 
6.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s78
14.2%
73
13.2%
r50
9.1%
o49
8.9%
i44
8.0%
e43
7.8%
a42
7.6%
u28
 
5.1%
n23
 
4.2%
d17
 
3.1%
Other values (17)104
18.9%
None
ValueCountFrequency (%)
ã19
54.3%
ç13
37.1%
á2
 
5.7%
ú1
 
2.9%

posicovid
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)3.7%
Missing3
Missing (%)5.3%
Memory size584.0 B
Não
44 
Sim
10 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters162
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowNão
3rd rowNão
4th rowNão
5th rowNão

Common Values

ValueCountFrequency (%)
Não44
77.2%
Sim10
 
17.5%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:47.495107image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:47.599832image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não44
81.5%
sim10
 
18.5%

Most occurring characters

ValueCountFrequency (%)
N44
27.2%
ã44
27.2%
o44
27.2%
S10
 
6.2%
i10
 
6.2%
m10
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter108
66.7%
Uppercase Letter54
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
ã44
40.7%
o44
40.7%
i10
 
9.3%
m10
 
9.3%
Uppercase Letter
ValueCountFrequency (%)
N44
81.5%
S10
 
18.5%

Most occurring scripts

ValueCountFrequency (%)
Latin162
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N44
27.2%
ã44
27.2%
o44
27.2%
S10
 
6.2%
i10
 
6.2%
m10
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII118
72.8%
None44
 
27.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N44
37.3%
o44
37.3%
S10
 
8.5%
i10
 
8.5%
m10
 
8.5%
None
ValueCountFrequency (%)
ã44
100.0%

quadcovid
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)20.0%
Missing47
Missing (%)82.5%
Memory size584.0 B
Leve, com pouco sintomas
Assintomático

Length

Max length24
Median length24
Mean length20.7
Min length13

Characters and Unicode

Total characters207
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLeve, com pouco sintomas
2nd rowLeve, com pouco sintomas
3rd rowAssintomático
4th rowLeve, com pouco sintomas
5th rowAssintomático

Common Values

ValueCountFrequency (%)
Leve, com pouco sintomas7
 
12.3%
Assintomático3
 
5.3%
(Missing)47
82.5%

Length

2022-05-31T15:05:47.697571image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:47.806278image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
leve7
22.6%
com7
22.6%
pouco7
22.6%
sintomas7
22.6%
assintomático3
9.7%

Most occurring characters

ValueCountFrequency (%)
o34
16.4%
21
10.1%
s20
9.7%
c17
8.2%
m17
8.2%
e14
 
6.8%
i13
 
6.3%
t13
 
6.3%
n10
 
4.8%
L7
 
3.4%
Other values (7)41
19.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter169
81.6%
Space Separator21
 
10.1%
Uppercase Letter10
 
4.8%
Other Punctuation7
 
3.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o34
20.1%
s20
11.8%
c17
10.1%
m17
10.1%
e14
8.3%
i13
 
7.7%
t13
 
7.7%
n10
 
5.9%
a7
 
4.1%
p7
 
4.1%
Other values (3)17
10.1%
Uppercase Letter
ValueCountFrequency (%)
L7
70.0%
A3
30.0%
Space Separator
ValueCountFrequency (%)
21
100.0%
Other Punctuation
ValueCountFrequency (%)
,7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin179
86.5%
Common28
 
13.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
o34
19.0%
s20
11.2%
c17
9.5%
m17
9.5%
e14
7.8%
i13
 
7.3%
t13
 
7.3%
n10
 
5.6%
L7
 
3.9%
a7
 
3.9%
Other values (5)27
15.1%
Common
ValueCountFrequency (%)
21
75.0%
,7
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII204
98.6%
None3
 
1.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o34
16.7%
21
10.3%
s20
9.8%
c17
8.3%
m17
8.3%
e14
 
6.9%
i13
 
6.4%
t13
 
6.4%
n10
 
4.9%
L7
 
3.4%
Other values (6)38
18.6%
None
ValueCountFrequency (%)
á3
100.0%

prcccovid
Categorical

HIGH CORRELATION
MISSING

Distinct9
Distinct (%)16.7%
Missing3
Missing (%)5.3%
Memory size584.0 B
Não
34 
Sim, por amigos ou familiares
Sim, por outros/terceiros
 
3
Sim, por amigos ou familiares Sim, por médicos particulares
 
2
Não Fiz tratamento precoce por conta própria
 
2
Other values (4)

Length

Max length70
Median length3
Mean length16.11111111
Min length3

Characters and Unicode

Total characters870
Distinct characters29
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)7.4%

Sample

1st rowSim, por amigos ou familiares Fiz tratamento precoce por conta própria
2nd rowNão
3rd rowNão
4th rowNão
5th rowNão

Common Values

ValueCountFrequency (%)
Não34
59.6%
Sim, por amigos ou familiares9
 
15.8%
Sim, por outros/terceiros3
 
5.3%
Sim, por amigos ou familiares Sim, por médicos particulares2
 
3.5%
Não Fiz tratamento precoce por conta própria2
 
3.5%
Sim, por amigos ou familiares Fiz tratamento precoce por conta própria1
 
1.8%
Fiz tratamento precoce por conta própria1
 
1.8%
Sim, por médicos do posto de saúde na minha comunidade/bairro1
 
1.8%
Sim, por amigos ou familiares Sim, por outros/terceiros1
 
1.8%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:47.923960image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:48.077558image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não36
23.2%
por24
15.5%
sim20
12.9%
amigos13
 
8.4%
ou13
 
8.4%
familiares13
 
8.4%
própria4
 
2.6%
conta4
 
2.6%
precoce4
 
2.6%
tratamento4
 
2.6%
Other values (11)20
12.9%

Most occurring characters

ValueCountFrequency (%)
o118
13.6%
101
11.6%
i79
 
9.1%
r71
 
8.2%
a64
 
7.4%
m55
 
6.3%
s41
 
4.7%
p39
 
4.5%
e38
 
4.4%
ã36
 
4.1%
Other values (19)228
26.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter684
78.6%
Space Separator101
 
11.6%
Uppercase Letter60
 
6.9%
Other Punctuation25
 
2.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o118
17.3%
i79
11.5%
r71
10.4%
a64
9.4%
m55
8.0%
s41
 
6.0%
p39
 
5.7%
e38
 
5.6%
ã36
 
5.3%
t27
 
3.9%
Other values (13)116
17.0%
Uppercase Letter
ValueCountFrequency (%)
N36
60.0%
S20
33.3%
F4
 
6.7%
Other Punctuation
ValueCountFrequency (%)
,20
80.0%
/5
 
20.0%
Space Separator
ValueCountFrequency (%)
101
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin744
85.5%
Common126
 
14.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
o118
15.9%
i79
10.6%
r71
9.5%
a64
 
8.6%
m55
 
7.4%
s41
 
5.5%
p39
 
5.2%
e38
 
5.1%
ã36
 
4.8%
N36
 
4.8%
Other values (16)167
22.4%
Common
ValueCountFrequency (%)
101
80.2%
,20
 
15.9%
/5
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII826
94.9%
None44
 
5.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o118
14.3%
101
12.2%
i79
9.6%
r71
 
8.6%
a64
 
7.7%
m55
 
6.7%
s41
 
5.0%
p39
 
4.7%
e38
 
4.6%
N36
 
4.4%
Other values (15)184
22.3%
None
ValueCountFrequency (%)
ã36
81.8%
ó4
 
9.1%
é3
 
6.8%
ú1
 
2.3%

violmed
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)5.6%
Missing3
Missing (%)5.3%
Memory size584.0 B
Não
33 
Sim
17 
Não percebi ou não tenho certeza

Length

Max length32
Median length3
Mean length5.148148148
Min length3

Characters and Unicode

Total characters278
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão
2nd rowSim
3rd rowNão percebi ou não tenho certeza
4th rowNão
5th rowNão

Common Values

ValueCountFrequency (%)
Não33
57.9%
Sim17
29.8%
Não percebi ou não tenho certeza4
 
7.0%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:48.270039image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:48.378753image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não41
55.4%
sim17
23.0%
percebi4
 
5.4%
ou4
 
5.4%
tenho4
 
5.4%
certeza4
 
5.4%

Most occurring characters

ValueCountFrequency (%)
o49
17.6%
ã41
14.7%
N37
13.3%
i21
7.6%
20
7.2%
e20
7.2%
S17
 
6.1%
m17
 
6.1%
n8
 
2.9%
t8
 
2.9%
Other values (8)40
14.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter204
73.4%
Uppercase Letter54
 
19.4%
Space Separator20
 
7.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o49
24.0%
ã41
20.1%
i21
10.3%
e20
9.8%
m17
 
8.3%
n8
 
3.9%
t8
 
3.9%
r8
 
3.9%
c8
 
3.9%
b4
 
2.0%
Other values (5)20
9.8%
Uppercase Letter
ValueCountFrequency (%)
N37
68.5%
S17
31.5%
Space Separator
ValueCountFrequency (%)
20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin258
92.8%
Common20
 
7.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
o49
19.0%
ã41
15.9%
N37
14.3%
i21
8.1%
e20
7.8%
S17
 
6.6%
m17
 
6.6%
n8
 
3.1%
t8
 
3.1%
r8
 
3.1%
Other values (7)32
12.4%
Common
ValueCountFrequency (%)
20
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII237
85.3%
None41
 
14.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o49
20.7%
N37
15.6%
i21
8.9%
20
8.4%
e20
8.4%
S17
 
7.2%
m17
 
7.2%
n8
 
3.4%
t8
 
3.4%
r8
 
3.4%
Other values (7)32
13.5%
None
ValueCountFrequency (%)
ã41
100.0%

tpviolmed
Categorical

HIGH CORRELATION
MISSING

Distinct8
Distinct (%)47.1%
Missing40
Missing (%)70.2%
Memory size584.0 B
LGBTfobia
LGBTfobia Violência psicológica
Violência ginecológica Agressão verbal/física
Agressão verbal/física Violência psicológica Psicofobia Assédio religioso Assédio sexual
Agressão verbal/física Violência psicológica
Other values (3)

Length

Max length88
Median length9
Mean length26.76470588
Min length9

Characters and Unicode

Total characters455
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)35.3%

Sample

1st rowLGBTfobia
2nd rowLGBTfobia
3rd rowLGBTfobia
4th rowViolência ginecológica Agressão verbal/física
5th rowLGBTfobia

Common Values

ValueCountFrequency (%)
LGBTfobia9
 
15.8%
LGBTfobia Violência psicológica2
 
3.5%
Violência ginecológica Agressão verbal/física1
 
1.8%
Agressão verbal/física Violência psicológica Psicofobia Assédio religioso Assédio sexual1
 
1.8%
Agressão verbal/física Violência psicológica1
 
1.8%
Violência ginecológica LGBTfobia1
 
1.8%
LGBTfobia Violência psicológica Psicofobia Assédio religioso1
 
1.8%
Violência obstétrica Violência ginecológica1
 
1.8%
(Missing)40
70.2%

Length

2022-05-31T15:05:48.501376image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:48.657003image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
lgbtfobia13
28.9%
violência9
20.0%
psicológica5
 
11.1%
ginecológica3
 
6.7%
agressão3
 
6.7%
verbal/física3
 
6.7%
assédio3
 
6.7%
psicofobia2
 
4.4%
religioso2
 
4.4%
sexual1
 
2.2%

Most occurring characters

ValueCountFrequency (%)
i62
13.6%
o45
 
9.9%
a40
 
8.8%
c31
 
6.8%
28
 
6.2%
s26
 
5.7%
l23
 
5.1%
b19
 
4.2%
f18
 
4.0%
g16
 
3.5%
Other values (22)147
32.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter355
78.0%
Uppercase Letter69
 
15.2%
Space Separator28
 
6.2%
Other Punctuation3
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i62
17.5%
o45
12.7%
a40
11.3%
c31
8.7%
s26
7.3%
l23
 
6.5%
b19
 
5.4%
f18
 
5.1%
g16
 
4.5%
e12
 
3.4%
Other values (13)63
17.7%
Uppercase Letter
ValueCountFrequency (%)
G13
18.8%
L13
18.8%
T13
18.8%
B13
18.8%
V9
13.0%
A6
8.7%
P2
 
2.9%
Space Separator
ValueCountFrequency (%)
28
100.0%
Other Punctuation
ValueCountFrequency (%)
/3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin424
93.2%
Common31
 
6.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
i62
14.6%
o45
 
10.6%
a40
 
9.4%
c31
 
7.3%
s26
 
6.1%
l23
 
5.4%
b19
 
4.5%
f18
 
4.2%
g16
 
3.8%
G13
 
3.1%
Other values (20)131
30.9%
Common
ValueCountFrequency (%)
28
90.3%
/3
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII428
94.1%
None27
 
5.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i62
14.5%
o45
 
10.5%
a40
 
9.3%
c31
 
7.2%
28
 
6.5%
s26
 
6.1%
l23
 
5.4%
b19
 
4.4%
f18
 
4.2%
g16
 
3.7%
Other values (17)120
28.0%
None
ValueCountFrequency (%)
ê9
33.3%
ó8
29.6%
é4
14.8%
í3
 
11.1%
ã3
 
11.1%

agrsidgen
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)5.6%
Missing3
Missing (%)5.3%
Memory size584.0 B
Não
29 
Sim, mais de uma vez
22 
Sim, uma vez

Length

Max length20
Median length3
Mean length10.42592593
Min length3

Characters and Unicode

Total characters563
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão
2nd rowSim, mais de uma vez
3rd rowNão
4th rowNão
5th rowNão

Common Values

ValueCountFrequency (%)
Não29
50.9%
Sim, mais de uma vez22
38.6%
Sim, uma vez3
 
5.3%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:48.844502image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:48.969124image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não29
19.6%
sim25
16.9%
uma25
16.9%
vez25
16.9%
mais22
14.9%
de22
14.9%

Most occurring characters

ValueCountFrequency (%)
94
16.7%
m72
12.8%
i47
 
8.3%
a47
 
8.3%
e47
 
8.3%
N29
 
5.2%
ã29
 
5.2%
o29
 
5.2%
S25
 
4.4%
,25
 
4.4%
Other values (5)119
21.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter390
69.3%
Space Separator94
 
16.7%
Uppercase Letter54
 
9.6%
Other Punctuation25
 
4.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
m72
18.5%
i47
12.1%
a47
12.1%
e47
12.1%
ã29
7.4%
o29
7.4%
u25
 
6.4%
v25
 
6.4%
z25
 
6.4%
s22
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
N29
53.7%
S25
46.3%
Space Separator
ValueCountFrequency (%)
94
100.0%
Other Punctuation
ValueCountFrequency (%)
,25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin444
78.9%
Common119
 
21.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
m72
16.2%
i47
10.6%
a47
10.6%
e47
10.6%
N29
6.5%
ã29
6.5%
o29
6.5%
S25
 
5.6%
u25
 
5.6%
v25
 
5.6%
Other values (3)69
15.5%
Common
ValueCountFrequency (%)
94
79.0%
,25
 
21.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII534
94.8%
None29
 
5.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
94
17.6%
m72
13.5%
i47
8.8%
a47
8.8%
e47
8.8%
N29
 
5.4%
o29
 
5.4%
S25
 
4.7%
,25
 
4.7%
u25
 
4.7%
Other values (4)94
17.6%
None
ValueCountFrequency (%)
ã29
100.0%

ondeagres
Categorical

HIGH CORRELATION
MISSING

Distinct15
Distinct (%)60.0%
Missing32
Missing (%)56.1%
Memory size584.0 B
Na comunidade onde vivo Na escola/universidade No trabalho No ambiente familiar Espaços públicos Transporte (táxi, uber, ônibus, metrô, trem etc.)
Espaços públicos
Na comunidade onde vivo Espaços públicos
Na comunidade onde vivo Na escola/universidade No trabalho No ambiente familiar
Na comunidade onde vivo
 
1
Other values (10)
10 

Length

Max length160
Median length123
Mean length83.12
Min length16

Characters and Unicode

Total characters2078
Distinct characters34
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)44.0%

Sample

1st rowNa comunidade onde vivo
2nd rowNa comunidade onde vivo Na escola/universidade No trabalho No ambiente familiar
3rd rowNa comunidade onde vivo Na escola/universidade No trabalho No ambiente familiar
4th rowNa escola/universidade No ambiente familiar Espaços públicos Transporte (táxi, uber, ônibus, metrô, trem etc.)
5th rowNa comunidade onde vivo No trabalho Espaços públicos Transporte (táxi, uber, ônibus, metrô, trem etc.)

Common Values

ValueCountFrequency (%)
Na comunidade onde vivo Na escola/universidade No trabalho No ambiente familiar Espaços públicos Transporte (táxi, uber, ônibus, metrô, trem etc.)5
 
8.8%
Espaços públicos4
 
7.0%
Na comunidade onde vivo Espaços públicos3
 
5.3%
Na comunidade onde vivo Na escola/universidade No trabalho No ambiente familiar2
 
3.5%
Na comunidade onde vivo1
 
1.8%
Na escola/universidade No ambiente familiar Espaços públicos Transporte (táxi, uber, ônibus, metrô, trem etc.)1
 
1.8%
Na comunidade onde vivo No trabalho Espaços públicos Transporte (táxi, uber, ônibus, metrô, trem etc.)1
 
1.8%
Na comunidade onde vivo No trabalho No ambiente familiar1
 
1.8%
Na comunidade onde vivo Na escola/universidade Espaços públicos1
 
1.8%
Na comunidade onde vivo No trabalho No ambiente familiar Espaços públicos Transporte (táxi, uber, ônibus, metrô, trem etc.)1
 
1.8%
Other values (5)5
 
8.8%
(Missing)32
56.1%

Length

2022-05-31T15:05:49.087849image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na30
 
10.4%
no24
 
8.3%
espaços21
 
7.3%
públicos21
 
7.3%
comunidade19
 
6.6%
onde18
 
6.2%
vivo18
 
6.2%
ambiente13
 
4.5%
familiar13
 
4.5%
ônibus12
 
4.2%
Other values (12)99
34.4%

Most occurring characters

ValueCountFrequency (%)
263
 
12.7%
a171
 
8.2%
e160
 
7.7%
o157
 
7.6%
i145
 
7.0%
s113
 
5.4%
r97
 
4.7%
t86
 
4.1%
n86
 
4.1%
d81
 
3.9%
Other values (24)719
34.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1630
78.4%
Space Separator263
 
12.7%
Uppercase Letter89
 
4.3%
Other Punctuation72
 
3.5%
Close Punctuation12
 
0.6%
Open Punctuation12
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a171
 
10.5%
e160
 
9.8%
o157
 
9.6%
i145
 
8.9%
s113
 
6.9%
r97
 
6.0%
t86
 
5.3%
n86
 
5.3%
d81
 
5.0%
m71
 
4.4%
Other values (14)463
28.4%
Uppercase Letter
ValueCountFrequency (%)
N54
60.7%
E21
 
23.6%
T12
 
13.5%
F2
 
2.2%
Other Punctuation
ValueCountFrequency (%)
,48
66.7%
/12
 
16.7%
.12
 
16.7%
Space Separator
ValueCountFrequency (%)
263
100.0%
Close Punctuation
ValueCountFrequency (%)
)12
100.0%
Open Punctuation
ValueCountFrequency (%)
(12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1719
82.7%
Common359
 
17.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a171
 
9.9%
e160
 
9.3%
o157
 
9.1%
i145
 
8.4%
s113
 
6.6%
r97
 
5.6%
t86
 
5.0%
n86
 
5.0%
d81
 
4.7%
m71
 
4.1%
Other values (18)552
32.1%
Common
ValueCountFrequency (%)
263
73.3%
,48
 
13.4%
/12
 
3.3%
)12
 
3.3%
.12
 
3.3%
(12
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII1999
96.2%
None79
 
3.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
263
13.2%
a171
 
8.6%
e160
 
8.0%
o157
 
7.9%
i145
 
7.3%
s113
 
5.7%
r97
 
4.9%
t86
 
4.3%
n86
 
4.3%
d81
 
4.1%
Other values (19)640
32.0%
None
ValueCountFrequency (%)
ô24
30.4%
ç21
26.6%
ú21
26.6%
á12
15.2%
é1
 
1.3%

usobanh
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)3.7%
Missing3
Missing (%)5.3%
Memory size584.0 B
Não
40 
Sim
14 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters162
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowSim
3rd rowSim
4th rowNão
5th rowNão

Common Values

ValueCountFrequency (%)
Não40
70.2%
Sim14
 
24.6%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:49.205535image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:49.318233image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não40
74.1%
sim14
 
25.9%

Most occurring characters

ValueCountFrequency (%)
N40
24.7%
ã40
24.7%
o40
24.7%
S14
 
8.6%
i14
 
8.6%
m14
 
8.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter108
66.7%
Uppercase Letter54
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
ã40
37.0%
o40
37.0%
i14
 
13.0%
m14
 
13.0%
Uppercase Letter
ValueCountFrequency (%)
N40
74.1%
S14
 
25.9%

Most occurring scripts

ValueCountFrequency (%)
Latin162
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N40
24.7%
ã40
24.7%
o40
24.7%
S14
 
8.6%
i14
 
8.6%
m14
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII122
75.3%
None40
 
24.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N40
32.8%
o40
32.8%
S14
 
11.5%
i14
 
11.5%
m14
 
11.5%
None
ValueCountFrequency (%)
ã40
100.0%

ondeocor
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct13
Distinct (%)92.9%
Missing43
Missing (%)75.4%
Memory size584.0 B
Na escola/universidade
No shopping
Na escola/universidade Festas
Na escola/universidade No shopping Espaços de lazer
Casa de show, festa.
Other values (8)

Length

Max length53
Median length22.5
Mean length24.71428571
Min length6

Characters and Unicode

Total characters346
Distinct characters36
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)85.7%

Sample

1st rowNo shopping
2nd rowNa escola/universidade Festas
3rd rowNa escola/universidade
4th rowNa escola/universidade No shopping Espaços de lazer
5th rowCasa de show, festa.

Common Values

ValueCountFrequency (%)
Na escola/universidade2
 
3.5%
No shopping1
 
1.8%
Na escola/universidade Festas1
 
1.8%
Na escola/universidade No shopping Espaços de lazer 1
 
1.8%
Casa de show, festa.1
 
1.8%
Na rua1
 
1.8%
Em um clube1
 
1.8%
Em um quiosque; Muriqui1
 
1.8%
Na quadra vila isabel1
 
1.8%
Na escola/universidade No trabalho No shopping Na rua1
 
1.8%
Other values (3)3
 
5.3%
(Missing)43
75.4%

Length

2022-05-31T15:05:49.419962image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na9
17.3%
escola/universidade6
 
11.5%
no5
 
9.6%
shopping3
 
5.8%
de3
 
5.8%
show2
 
3.8%
trabalho2
 
3.8%
um2
 
3.8%
rua2
 
3.8%
em2
 
3.8%
Other values (15)16
30.8%

Most occurring characters

ValueCountFrequency (%)
a44
12.7%
39
 
11.3%
e30
 
8.7%
s26
 
7.5%
o22
 
6.4%
i20
 
5.8%
u19
 
5.5%
d16
 
4.6%
r15
 
4.3%
N15
 
4.3%
Other values (26)100
28.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter273
78.9%
Space Separator39
 
11.3%
Uppercase Letter25
 
7.2%
Other Punctuation9
 
2.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a44
16.1%
e30
11.0%
s26
9.5%
o22
 
8.1%
i20
 
7.3%
u19
 
7.0%
d16
 
5.9%
r15
 
5.5%
l13
 
4.8%
n10
 
3.7%
Other values (13)58
21.2%
Uppercase Letter
ValueCountFrequency (%)
N15
60.0%
E3
 
12.0%
C2
 
8.0%
R1
 
4.0%
S1
 
4.0%
M1
 
4.0%
F1
 
4.0%
P1
 
4.0%
Other Punctuation
ValueCountFrequency (%)
/6
66.7%
;1
 
11.1%
.1
 
11.1%
,1
 
11.1%
Space Separator
ValueCountFrequency (%)
39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin298
86.1%
Common48
 
13.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a44
14.8%
e30
 
10.1%
s26
 
8.7%
o22
 
7.4%
i20
 
6.7%
u19
 
6.4%
d16
 
5.4%
r15
 
5.0%
N15
 
5.0%
l13
 
4.4%
Other values (21)78
26.2%
Common
ValueCountFrequency (%)
39
81.2%
/6
 
12.5%
;1
 
2.1%
.1
 
2.1%
,1
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII345
99.7%
None1
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a44
12.8%
39
 
11.3%
e30
 
8.7%
s26
 
7.5%
o22
 
6.4%
i20
 
5.8%
u19
 
5.5%
d16
 
4.6%
r15
 
4.3%
N15
 
4.3%
Other values (25)99
28.7%
None
ValueCountFrequency (%)
ç1
100.0%

violsex
Categorical

HIGH CORRELATION
MISSING

Distinct9
Distinct (%)17.0%
Missing4
Missing (%)7.0%
Memory size584.0 B
Não, nunca.
28 
Sim, na infância
Sim, na infância Sim, na adolescência Sim, na vida adulta
Sim, na adolescência
Sim, na infância Sim, na adolescência
 
2
Other values (4)

Length

Max length57
Median length11
Mean length20.1509434
Min length11

Characters and Unicode

Total characters1068
Distinct characters25
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)7.5%

Sample

1st rowNão, nunca.
2nd rowNão, nunca.
3rd rowNão, nunca.
4th rowNão, nunca.
5th rowNão, nunca.

Common Values

ValueCountFrequency (%)
Não, nunca.28
49.1%
Sim, na infância9
 
15.8%
Sim, na infância Sim, na adolescência Sim, na vida adulta6
 
10.5%
Sim, na adolescência4
 
7.0%
Sim, na infância Sim, na adolescência2
 
3.5%
Não, mas já tentaram1
 
1.8%
Sim, na vida adulta1
 
1.8%
Sim, na adolescência Sim, na vida adulta1
 
1.8%
Sim, na adolescência Não, mas já tentaram1
 
1.8%
(Missing)4
 
7.0%

Length

2022-05-31T15:05:49.541633image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:49.683257image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim39
20.6%
na39
20.6%
não30
15.9%
nunca28
14.8%
infância17
9.0%
adolescência14
 
7.4%
vida8
 
4.2%
adulta8
 
4.2%
mas2
 
1.1%
2
 
1.1%

Most occurring characters

ValueCountFrequency (%)
n145
13.6%
a142
13.3%
136
12.7%
i95
 
8.9%
c73
 
6.8%
,69
 
6.5%
o44
 
4.1%
m43
 
4.0%
S39
 
3.7%
u36
 
3.4%
Other values (15)246
23.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter766
71.7%
Space Separator136
 
12.7%
Other Punctuation97
 
9.1%
Uppercase Letter69
 
6.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n145
18.9%
a142
18.5%
i95
12.4%
c73
9.5%
o44
 
5.7%
m43
 
5.6%
u36
 
4.7%
ã30
 
3.9%
d30
 
3.9%
l22
 
2.9%
Other values (10)106
13.8%
Other Punctuation
ValueCountFrequency (%)
,69
71.1%
.28
28.9%
Uppercase Letter
ValueCountFrequency (%)
S39
56.5%
N30
43.5%
Space Separator
ValueCountFrequency (%)
136
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin835
78.2%
Common233
 
21.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
n145
17.4%
a142
17.0%
i95
11.4%
c73
8.7%
o44
 
5.3%
m43
 
5.1%
S39
 
4.7%
u36
 
4.3%
ã30
 
3.6%
d30
 
3.6%
Other values (12)158
18.9%
Common
ValueCountFrequency (%)
136
58.4%
,69
29.6%
.28
 
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1005
94.1%
None63
 
5.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n145
14.4%
a142
14.1%
136
13.5%
i95
9.5%
c73
 
7.3%
,69
 
6.9%
o44
 
4.4%
m43
 
4.3%
S39
 
3.9%
u36
 
3.6%
Other values (11)183
18.2%
None
ValueCountFrequency (%)
ã30
47.6%
â17
27.0%
ê14
22.2%
á2
 
3.2%

ondviolsex
Categorical

HIGH CORRELATION
MISSING

Distinct14
Distinct (%)58.3%
Missing33
Missing (%)57.9%
Memory size584.0 B
Na casa de parentes
Na rua
Outros
Na casa de vizinhos
Na casa de parentes Trabalho
Other values (9)

Length

Max length94
Median length85
Mean length23.58333333
Min length6

Characters and Unicode

Total characters566
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)41.7%

Sample

1st rowNa casa de parentes Trabalho
2nd rowNa rua
3rd rowNa casa de parentes
4th rowNa casa de parentes
5th rowNa casa de parentes

Common Values

ValueCountFrequency (%)
Na casa de parentes6
 
10.5%
Na rua4
 
7.0%
Outros2
 
3.5%
Na casa de vizinhos2
 
3.5%
Na casa de parentes Trabalho1
 
1.8%
Na casa de parentes Na casa de amigos Na rua Escola/universidade Trabalho Transporte Em festas1
 
1.8%
Na rua Escola/universidade Outros1
 
1.8%
Trabalho Outros1
 
1.8%
Trabalho Transporte1
 
1.8%
Na casa de parentes Na casa de vizinhos Outros1
 
1.8%
Other values (4)4
 
7.0%
(Missing)33
57.9%

Length

2022-05-31T15:05:49.847816image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na25
23.6%
casa16
15.1%
de16
15.1%
parentes10
 
9.4%
rua9
 
8.5%
outros6
 
5.7%
vizinhos5
 
4.7%
trabalho5
 
4.7%
em4
 
3.8%
festas4
 
3.8%
Other values (3)6
 
5.7%

Most occurring characters

ValueCountFrequency (%)
a99
17.5%
82
14.5%
s54
 
9.5%
e48
 
8.5%
r37
 
6.5%
N25
 
4.4%
t22
 
3.9%
o22
 
3.9%
d22
 
3.9%
n20
 
3.5%
Other values (16)135
23.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter436
77.0%
Space Separator82
 
14.5%
Uppercase Letter45
 
8.0%
Other Punctuation3
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a99
22.7%
s54
12.4%
e48
11.0%
r37
 
8.5%
t22
 
5.0%
o22
 
5.0%
d22
 
5.0%
n20
 
4.6%
c19
 
4.4%
u18
 
4.1%
Other values (10)75
17.2%
Uppercase Letter
ValueCountFrequency (%)
N25
55.6%
T7
 
15.6%
E7
 
15.6%
O6
 
13.3%
Space Separator
ValueCountFrequency (%)
82
100.0%
Other Punctuation
ValueCountFrequency (%)
/3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin481
85.0%
Common85
 
15.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a99
20.6%
s54
11.2%
e48
10.0%
r37
 
7.7%
N25
 
5.2%
t22
 
4.6%
o22
 
4.6%
d22
 
4.6%
n20
 
4.2%
c19
 
4.0%
Other values (14)113
23.5%
Common
ValueCountFrequency (%)
82
96.5%
/3
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII566
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a99
17.5%
82
14.5%
s54
 
9.5%
e48
 
8.5%
r37
 
6.5%
N25
 
4.4%
t22
 
3.9%
o22
 
3.9%
d22
 
3.9%
n20
 
3.5%
Other values (16)135
23.9%

expidgen
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)7.4%
Missing3
Missing (%)5.3%
Memory size584.0 B
Não
35 
Sim, uma vez
13 
Sim, mais de uma vez
Prefiro não responder
 
2

Length

Max length21
Median length3
Mean length7.092592593
Min length3

Characters and Unicode

Total characters383
Distinct characters20
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão
2nd rowNão
3rd rowNão
4th rowPrefiro não responder
5th rowSim, uma vez

Common Values

ValueCountFrequency (%)
Não35
61.4%
Sim, uma vez13
 
22.8%
Sim, mais de uma vez4
 
7.0%
Prefiro não responder2
 
3.5%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:49.967455image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:50.099146image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não37
37.0%
sim17
17.0%
uma17
17.0%
vez17
17.0%
mais4
 
4.0%
de4
 
4.0%
prefiro2
 
2.0%
responder2
 
2.0%

Most occurring characters

ValueCountFrequency (%)
46
12.0%
o41
10.7%
m38
9.9%
ã37
9.7%
N35
9.1%
e27
 
7.0%
i23
 
6.0%
a21
 
5.5%
z17
 
4.4%
v17
 
4.4%
Other values (10)81
21.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter266
69.5%
Uppercase Letter54
 
14.1%
Space Separator46
 
12.0%
Other Punctuation17
 
4.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o41
15.4%
m38
14.3%
ã37
13.9%
e27
10.2%
i23
8.6%
a21
7.9%
z17
6.4%
v17
6.4%
u17
6.4%
r8
 
3.0%
Other values (5)20
7.5%
Uppercase Letter
ValueCountFrequency (%)
N35
64.8%
S17
31.5%
P2
 
3.7%
Space Separator
ValueCountFrequency (%)
46
100.0%
Other Punctuation
ValueCountFrequency (%)
,17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin320
83.6%
Common63
 
16.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
o41
12.8%
m38
11.9%
ã37
11.6%
N35
10.9%
e27
8.4%
i23
7.2%
a21
6.6%
z17
 
5.3%
v17
 
5.3%
u17
 
5.3%
Other values (8)47
14.7%
Common
ValueCountFrequency (%)
46
73.0%
,17
 
27.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII346
90.3%
None37
 
9.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
46
13.3%
o41
11.8%
m38
11.0%
N35
10.1%
e27
7.8%
i23
 
6.6%
a21
 
6.1%
z17
 
4.9%
v17
 
4.9%
u17
 
4.9%
Other values (9)64
18.5%
None
ValueCountFrequency (%)
ã37
100.0%

centrolgbti
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)3.7%
Missing3
Missing (%)5.3%
Memory size584.0 B
Não
43 
Sim
11 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters162
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão
2nd rowNão
3rd rowNão
4th rowNão
5th rowNão

Common Values

ValueCountFrequency (%)
Não43
75.4%
Sim11
 
19.3%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:50.217784image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:50.347438image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não43
79.6%
sim11
 
20.4%

Most occurring characters

ValueCountFrequency (%)
N43
26.5%
ã43
26.5%
o43
26.5%
S11
 
6.8%
i11
 
6.8%
m11
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter108
66.7%
Uppercase Letter54
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
ã43
39.8%
o43
39.8%
i11
 
10.2%
m11
 
10.2%
Uppercase Letter
ValueCountFrequency (%)
N43
79.6%
S11
 
20.4%

Most occurring scripts

ValueCountFrequency (%)
Latin162
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N43
26.5%
ã43
26.5%
o43
26.5%
S11
 
6.8%
i11
 
6.8%
m11
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII119
73.5%
None43
 
26.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N43
36.1%
o43
36.1%
S11
 
9.2%
i11
 
9.2%
m11
 
9.2%
None
ValueCountFrequency (%)
ã43
100.0%

violverb
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)7.4%
Missing3
Missing (%)5.3%
Memory size584.0 B
Sim, inúmeras vezes
40 
Não
Sim, uma vez
Não tenho certeza/Não percebi
 
2

Length

Max length29
Median length19
Mean length16.81481481
Min length3

Characters and Unicode

Total characters908
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão tenho certeza/Não percebi
2nd rowSim, inúmeras vezes
3rd rowSim, inúmeras vezes
4th rowSim, inúmeras vezes
5th rowNão tenho certeza/Não percebi

Common Values

ValueCountFrequency (%)
Sim, inúmeras vezes40
70.2%
Não6
 
10.5%
Sim, uma vez6
 
10.5%
Não tenho certeza/Não percebi2
 
3.5%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:50.499034image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:50.638032image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim46
30.3%
inúmeras40
26.3%
vezes40
26.3%
não8
 
5.3%
uma6
 
3.9%
vez6
 
3.9%
tenho2
 
1.3%
certeza/não2
 
1.3%
percebi2
 
1.3%

Most occurring characters

ValueCountFrequency (%)
e136
15.0%
98
10.8%
m92
10.1%
i88
9.7%
s80
8.8%
a48
 
5.3%
z48
 
5.3%
S46
 
5.1%
v46
 
5.1%
,46
 
5.1%
Other values (13)180
19.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter706
77.8%
Space Separator98
 
10.8%
Uppercase Letter56
 
6.2%
Other Punctuation48
 
5.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e136
19.3%
m92
13.0%
i88
12.5%
s80
11.3%
a48
 
6.8%
z48
 
6.8%
v46
 
6.5%
r44
 
6.2%
n42
 
5.9%
ú40
 
5.7%
Other values (8)42
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
S46
82.1%
N10
 
17.9%
Other Punctuation
ValueCountFrequency (%)
,46
95.8%
/2
 
4.2%
Space Separator
ValueCountFrequency (%)
98
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin762
83.9%
Common146
 
16.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e136
17.8%
m92
12.1%
i88
11.5%
s80
10.5%
a48
 
6.3%
z48
 
6.3%
S46
 
6.0%
v46
 
6.0%
r44
 
5.8%
n42
 
5.5%
Other values (10)92
12.1%
Common
ValueCountFrequency (%)
98
67.1%
,46
31.5%
/2
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII858
94.5%
None50
 
5.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e136
15.9%
98
11.4%
m92
10.7%
i88
10.3%
s80
9.3%
a48
 
5.6%
z48
 
5.6%
S46
 
5.4%
v46
 
5.4%
,46
 
5.4%
Other values (11)130
15.2%
None
ValueCountFrequency (%)
ú40
80.0%
ã10
 
20.0%

piadidgen
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)7.4%
Missing3
Missing (%)5.3%
Memory size584.0 B
Sim, inúmeras vezes
37 
Sim, uma vez
10 
Não
Não tenho certeza/Não percebi
 
1

Length

Max length29
Median length19
Mean length16.11111111
Min length3

Characters and Unicode

Total characters870
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st rowSim, uma vez
2nd rowSim, uma vez
3rd rowSim, inúmeras vezes
4th rowSim, inúmeras vezes
5th rowSim, inúmeras vezes

Common Values

ValueCountFrequency (%)
Sim, inúmeras vezes37
64.9%
Sim, uma vez10
 
17.5%
Não6
 
10.5%
Não tenho certeza/Não percebi1
 
1.8%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:50.757670image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:50.876398image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim47
31.1%
inúmeras37
24.5%
vezes37
24.5%
uma10
 
6.6%
vez10
 
6.6%
não7
 
4.6%
tenho1
 
0.7%
certeza/não1
 
0.7%
percebi1
 
0.7%

Most occurring characters

ValueCountFrequency (%)
e126
14.5%
97
11.1%
m94
10.8%
i85
9.8%
s74
8.5%
a48
 
5.5%
z48
 
5.5%
S47
 
5.4%
v47
 
5.4%
,47
 
5.4%
Other values (13)157
18.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter670
77.0%
Space Separator97
 
11.1%
Uppercase Letter55
 
6.3%
Other Punctuation48
 
5.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e126
18.8%
m94
14.0%
i85
12.7%
s74
11.0%
a48
 
7.2%
z48
 
7.2%
v47
 
7.0%
r39
 
5.8%
n38
 
5.7%
ú37
 
5.5%
Other values (8)34
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
S47
85.5%
N8
 
14.5%
Other Punctuation
ValueCountFrequency (%)
,47
97.9%
/1
 
2.1%
Space Separator
ValueCountFrequency (%)
97
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin725
83.3%
Common145
 
16.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e126
17.4%
m94
13.0%
i85
11.7%
s74
10.2%
a48
 
6.6%
z48
 
6.6%
S47
 
6.5%
v47
 
6.5%
r39
 
5.4%
n38
 
5.2%
Other values (10)79
10.9%
Common
ValueCountFrequency (%)
97
66.9%
,47
32.4%
/1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII825
94.8%
None45
 
5.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e126
15.3%
97
11.8%
m94
11.4%
i85
10.3%
s74
9.0%
a48
 
5.8%
z48
 
5.8%
S47
 
5.7%
v47
 
5.7%
,47
 
5.7%
Other values (11)112
13.6%
None
ValueCountFrequency (%)
ú37
82.2%
ã8
 
17.8%

idgenexpo
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)7.4%
Missing3
Missing (%)5.3%
Memory size584.0 B
Sim, inúmeras vezes
28 
Não
16 
Sim, uma vez
Não tenho certeza/Não percebi

Length

Max length29
Median length19
Mean length14.53703704
Min length3

Characters and Unicode

Total characters785
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim, uma vez
2nd rowNão
3rd rowNão tenho certeza/Não percebi
4th rowSim, inúmeras vezes
5th rowSim, inúmeras vezes

Common Values

ValueCountFrequency (%)
Sim, inúmeras vezes28
49.1%
Não16
28.1%
Sim, uma vez5
 
8.8%
Não tenho certeza/Não percebi5
 
8.8%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:50.991090image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:51.116710image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim33
24.4%
inúmeras28
20.7%
vezes28
20.7%
não21
15.6%
uma5
 
3.7%
vez5
 
3.7%
tenho5
 
3.7%
certeza/não5
 
3.7%
percebi5
 
3.7%

Most occurring characters

ValueCountFrequency (%)
e114
14.5%
81
 
10.3%
m66
 
8.4%
i66
 
8.4%
s56
 
7.1%
a38
 
4.8%
z38
 
4.8%
r38
 
4.8%
S33
 
4.2%
v33
 
4.2%
Other values (13)222
28.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter607
77.3%
Space Separator81
 
10.3%
Uppercase Letter59
 
7.5%
Other Punctuation38
 
4.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e114
18.8%
m66
10.9%
i66
10.9%
s56
9.2%
a38
 
6.3%
z38
 
6.3%
r38
 
6.3%
v33
 
5.4%
n33
 
5.4%
o31
 
5.1%
Other values (8)94
15.5%
Uppercase Letter
ValueCountFrequency (%)
S33
55.9%
N26
44.1%
Other Punctuation
ValueCountFrequency (%)
,33
86.8%
/5
 
13.2%
Space Separator
ValueCountFrequency (%)
81
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin666
84.8%
Common119
 
15.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e114
17.1%
m66
9.9%
i66
9.9%
s56
 
8.4%
a38
 
5.7%
z38
 
5.7%
r38
 
5.7%
S33
 
5.0%
v33
 
5.0%
n33
 
5.0%
Other values (10)151
22.7%
Common
ValueCountFrequency (%)
81
68.1%
,33
27.7%
/5
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII731
93.1%
None54
 
6.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e114
15.6%
81
11.1%
m66
 
9.0%
i66
 
9.0%
s56
 
7.7%
a38
 
5.2%
z38
 
5.2%
r38
 
5.2%
S33
 
4.5%
v33
 
4.5%
Other values (11)168
23.0%
None
ValueCountFrequency (%)
ú28
51.9%
ã26
48.1%

usocentr
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)3.7%
Missing3
Missing (%)5.3%
Memory size584.0 B
Não
43 
Sim
11 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters162
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão
2nd rowNão
3rd rowNão
4th rowNão
5th rowNão

Common Values

ValueCountFrequency (%)
Não43
75.4%
Sim11
 
19.3%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:51.233437image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:51.344102image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não43
79.6%
sim11
 
20.4%

Most occurring characters

ValueCountFrequency (%)
N43
26.5%
ã43
26.5%
o43
26.5%
S11
 
6.8%
i11
 
6.8%
m11
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter108
66.7%
Uppercase Letter54
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
ã43
39.8%
o43
39.8%
i11
 
10.2%
m11
 
10.2%
Uppercase Letter
ValueCountFrequency (%)
N43
79.6%
S11
 
20.4%

Most occurring scripts

ValueCountFrequency (%)
Latin162
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N43
26.5%
ã43
26.5%
o43
26.5%
S11
 
6.8%
i11
 
6.8%
m11
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII119
73.5%
None43
 
26.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N43
36.1%
o43
36.1%
S11
 
9.2%
i11
 
9.2%
m11
 
9.2%
None
ValueCountFrequency (%)
ã43
100.0%

motnaocentr
Categorical

HIGH CORRELATION
MISSING

Distinct14
Distinct (%)35.0%
Missing17
Missing (%)29.8%
Memory size584.0 B
Prefiro não dizer
14 
Não acredito que esse tipo de serviço funcione (credibilidade)
Fica longe da minha casa (acesso)
Tenho medo de represálias (segurança pessoal)
Não houve necessidade
 
1
Other values (9)

Length

Max length62
Median length45
Mean length30.25
Min length8

Characters and Unicode

Total characters1210
Distinct characters35
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)25.0%

Sample

1st rowFica longe da minha casa (acesso)
2nd rowNão acredito que esse tipo de serviço funcione (credibilidade)
3rd rowPrefiro não dizer
4th rowTenho medo de represálias (segurança pessoal)
5th rowNão acredito que esse tipo de serviço funcione (credibilidade)

Common Values

ValueCountFrequency (%)
Prefiro não dizer14
24.6%
Não acredito que esse tipo de serviço funcione (credibilidade)8
14.0%
Fica longe da minha casa (acesso)6
 
10.5%
Tenho medo de represálias (segurança pessoal)2
 
3.5%
Não houve necessidade1
 
1.8%
não conheço nenhum1
 
1.8%
Não sabia 1
 
1.8%
Lá onde moro não tem esse recurso1
 
1.8%
Não conhecia1
 
1.8%
Só nunca procurei1
 
1.8%
Other values (4)4
 
7.0%
(Missing)17
29.8%

Length

2022-05-31T15:05:51.448864image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
não31
 
15.8%
prefiro14
 
7.1%
dizer14
 
7.1%
de10
 
5.1%
esse9
 
4.6%
acredito8
 
4.1%
que8
 
4.1%
tipo8
 
4.1%
serviço8
 
4.1%
funcione8
 
4.1%
Other values (34)78
39.8%

Most occurring characters

ValueCountFrequency (%)
158
13.1%
e148
12.2%
o109
 
9.0%
i105
 
8.7%
r82
 
6.8%
a68
 
5.6%
d68
 
5.6%
s65
 
5.4%
n62
 
5.1%
c52
 
4.3%
Other values (25)293
24.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter982
81.2%
Space Separator158
 
13.1%
Uppercase Letter37
 
3.1%
Close Punctuation16
 
1.3%
Open Punctuation16
 
1.3%
Other Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e148
15.1%
o109
11.1%
i105
10.7%
r82
8.4%
a68
 
6.9%
d68
 
6.9%
s65
 
6.6%
n62
 
6.3%
c52
 
5.3%
ã31
 
3.2%
Other values (15)192
19.6%
Uppercase Letter
ValueCountFrequency (%)
P14
37.8%
N13
35.1%
F6
16.2%
T2
 
5.4%
L1
 
2.7%
S1
 
2.7%
Space Separator
ValueCountFrequency (%)
158
100.0%
Close Punctuation
ValueCountFrequency (%)
)16
100.0%
Open Punctuation
ValueCountFrequency (%)
(16
100.0%
Other Punctuation
ValueCountFrequency (%)
.1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1019
84.2%
Common191
 
15.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e148
14.5%
o109
10.7%
i105
10.3%
r82
 
8.0%
a68
 
6.7%
d68
 
6.7%
s65
 
6.4%
n62
 
6.1%
c52
 
5.1%
ã31
 
3.0%
Other values (21)229
22.5%
Common
ValueCountFrequency (%)
158
82.7%
)16
 
8.4%
(16
 
8.4%
.1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII1163
96.1%
None47
 
3.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
158
13.6%
e148
12.7%
o109
9.4%
i105
9.0%
r82
 
7.1%
a68
 
5.8%
d68
 
5.8%
s65
 
5.6%
n62
 
5.3%
c52
 
4.5%
Other values (21)246
21.2%
None
ValueCountFrequency (%)
ã31
66.0%
ç12
 
25.5%
á3
 
6.4%
ó1
 
2.1%

agresstp
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct39
Distinct (%)81.2%
Missing9
Missing (%)15.8%
Memory size584.0 B
Um familiar
Homem na rua
 
3
Homem da minha comunidade
 
2
Homem da minha comunidade Homem na rua
 
2
Agente público de segurança (policial militar, civil, guarda municipal, polícia federal etc) Homem da minha comunidade Mulher da minha comunidade Homem na rua
 
2
Other values (34)
35 

Length

Max length441
Median length126
Mean length120.2916667
Min length11

Characters and Unicode

Total characters5774
Distinct characters42
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)68.8%

Sample

1st rowAgente público da educação (professor/a, diretor/a, coordenador pedagógico, etc) Homem na rua
2nd rowHomem da minha comunidade
3rd rowHomem da minha comunidade Homem na rua
4th rowSofri uma agressão virtual por desconhecido/ perfil fake
5th rowAgente público de segurança (policial militar, civil, guarda municipal, polícia federal etc) Homem da minha comunidade Mulher da minha comunidade Homem na rua

Common Values

ValueCountFrequency (%)
Um familiar4
 
7.0%
Homem na rua3
 
5.3%
Homem da minha comunidade2
 
3.5%
Homem da minha comunidade Homem na rua2
 
3.5%
Agente público de segurança (policial militar, civil, guarda municipal, polícia federal etc) Homem da minha comunidade Mulher da minha comunidade Homem na rua2
 
3.5%
Homem da minha comunidade Mulher da minha comunidade Homem na rua Mulher na rua2
 
3.5%
Agente público de segurança (policial militar, civil, guarda municipal, polícia federal etc) Agente público da saúde (médico/a, enfermeiro/a, técnico/a em enfermagem, maqueiro, etc) Homem da minha comunidade Mulher na rua Sofri uma agressão virtual por desconhecido/ perfil fake1
 
1.8%
Agente público da educação (professor/a, diretor/a, coordenador pedagógico, etc) Um familiar Homem na rua1
 
1.8%
Homem da minha comunidade Mulher da minha comunidade Homem na rua Mulher na rua Funcionário/a de empresa/loja1
 
1.8%
Agente público da saúde (médico/a, enfermeiro/a, técnico/a em enfermagem, maqueiro, etc) Homem da minha comunidade Mulher da minha comunidade Um familiar Homem na rua Mulher na rua Funcionário/a de empresa/loja Sofri uma agressão virtual por desconhecido/ perfil fake1
 
1.8%
Other values (29)29
50.9%
(Missing)9
 
15.8%

Length

2022-05-31T15:05:51.587451image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
da60
 
7.2%
homem58
 
7.0%
na45
 
5.4%
rua44
 
5.3%
minha44
 
5.3%
comunidade44
 
5.3%
mulher30
 
3.6%
etc29
 
3.5%
público29
 
3.5%
agente29
 
3.5%
Other values (38)416
50.2%

Most occurring characters

ValueCountFrequency (%)
780
13.5%
a580
 
10.0%
e504
 
8.7%
i410
 
7.1%
o365
 
6.3%
m346
 
6.0%
r326
 
5.6%
d285
 
4.9%
n261
 
4.5%
c246
 
4.3%
Other values (32)1671
28.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4596
79.6%
Space Separator780
 
13.5%
Other Punctuation176
 
3.0%
Uppercase Letter164
 
2.8%
Open Punctuation29
 
0.5%
Close Punctuation29
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a580
12.6%
e504
11.0%
i410
 
8.9%
o365
 
7.9%
m346
 
7.5%
r326
 
7.1%
d285
 
6.2%
n261
 
5.7%
c246
 
5.4%
u216
 
4.7%
Other values (20)1057
23.0%
Uppercase Letter
ValueCountFrequency (%)
H58
35.4%
M30
18.3%
A29
17.7%
U18
 
11.0%
S16
 
9.8%
F11
 
6.7%
P2
 
1.2%
Other Punctuation
ValueCountFrequency (%)
,96
54.5%
/80
45.5%
Space Separator
ValueCountFrequency (%)
780
100.0%
Open Punctuation
ValueCountFrequency (%)
(29
100.0%
Close Punctuation
ValueCountFrequency (%)
)29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4760
82.4%
Common1014
 
17.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a580
12.2%
e504
10.6%
i410
 
8.6%
o365
 
7.7%
m346
 
7.3%
r326
 
6.8%
d285
 
6.0%
n261
 
5.5%
c246
 
5.2%
u216
 
4.5%
Other values (27)1221
25.7%
Common
ValueCountFrequency (%)
780
76.9%
,96
 
9.5%
/80
 
7.9%
(29
 
2.9%
)29
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII5643
97.7%
None131
 
2.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
780
13.8%
a580
 
10.3%
e504
 
8.9%
i410
 
7.3%
o365
 
6.5%
m346
 
6.1%
r326
 
5.8%
d285
 
5.1%
n261
 
4.6%
c246
 
4.4%
Other values (24)1540
27.3%
None
ValueCountFrequency (%)
ú38
29.0%
ã23
17.6%
ç20
15.3%
é18
13.7%
í13
 
9.9%
á11
 
8.4%
ó7
 
5.3%
ê1
 
0.8%

classagrs
Categorical

HIGH CORRELATION
MISSING

Distinct23
Distinct (%)47.9%
Missing9
Missing (%)15.8%
Memory size584.0 B
Verbalmente/ com xingamentos
12 
Verbalmente/ com xingamentos Fisicamente, com tapas, chutes, soco e pontapés
Verbalmente/ com xingamentos Fisicamente, com tapas, chutes, soco e pontapés Fisicamente, com uma madeira ou objeto Fisicamente, sexualmente Fisicamente, com uma faca ou objeto cortante Fisicamente, com uma arma de fogo Virtualmente
Virtualmente
Verbalmente/ com xingamentos Fisicamente, com tapas, chutes, soco e pontapés Virtualmente
 
2
Other values (18)
22 

Length

Max length232
Median length154.5
Mean length78.3125
Min length12

Characters and Unicode

Total characters3759
Distinct characters28
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)29.2%

Sample

1st rowFisicamente, com uma madeira ou objeto Virtualmente
2nd rowFisicamente, com tapas, chutes, soco e pontapés
3rd rowVerbalmente/ com xingamentos
4th rowVirtualmente
5th rowVerbalmente/ com xingamentos Fisicamente, com tapas, chutes, soco e pontapés

Common Values

ValueCountFrequency (%)
Verbalmente/ com xingamentos12
21.1%
Verbalmente/ com xingamentos Fisicamente, com tapas, chutes, soco e pontapés6
10.5%
Verbalmente/ com xingamentos Fisicamente, com tapas, chutes, soco e pontapés Fisicamente, com uma madeira ou objeto Fisicamente, sexualmente Fisicamente, com uma faca ou objeto cortante Fisicamente, com uma arma de fogo Virtualmente3
 
5.3%
Virtualmente3
 
5.3%
Verbalmente/ com xingamentos Fisicamente, com tapas, chutes, soco e pontapés Virtualmente2
 
3.5%
Verbalmente/ com xingamentos Fisicamente, com tapas, chutes, soco e pontapés Fisicamente, sexualmente Fisicamente, com uma arma de fogo Virtualmente2
 
3.5%
Verbalmente/ com xingamentos Fisicamente, com tapas, chutes, soco e pontapés Fisicamente, com uma madeira ou objeto Fisicamente, sexualmente Fisicamente, com uma arma de fogo Virtualmente2
 
3.5%
Verbalmente/ com xingamentos Virtualmente2
 
3.5%
Verbalmente/ com xingamentos Fisicamente, sexualmente2
 
3.5%
Verbalmente/ com xingamentos Fisicamente, com uma madeira ou objeto Fisicamente, sexualmente Fisicamente, com uma faca ou objeto cortante Virtualmente1
 
1.8%
Other values (13)13
22.8%
(Missing)9
15.8%

Length

2022-05-31T15:05:51.732064image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
com86
18.0%
fisicamente62
13.0%
verbalmente40
 
8.4%
xingamentos40
 
8.4%
uma27
 
5.7%
tapas19
 
4.0%
chutes19
 
4.0%
soco19
 
4.0%
e19
 
4.0%
pontapés19
 
4.0%
Other values (12)127
26.6%

Most occurring characters

ValueCountFrequency (%)
e454
12.1%
430
11.4%
a326
 
8.7%
m309
 
8.2%
t290
 
7.7%
o265
 
7.0%
n246
 
6.5%
c205
 
5.5%
s197
 
5.2%
i196
 
5.2%
Other values (18)841
22.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3067
81.6%
Space Separator430
 
11.4%
Other Punctuation140
 
3.7%
Uppercase Letter122
 
3.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e454
14.8%
a326
10.6%
m309
10.1%
t290
9.5%
o265
8.6%
n246
8.0%
c205
6.7%
s197
6.4%
i196
6.4%
u99
 
3.2%
Other values (12)480
15.7%
Uppercase Letter
ValueCountFrequency (%)
F62
50.8%
V59
48.4%
O1
 
0.8%
Other Punctuation
ValueCountFrequency (%)
,100
71.4%
/40
 
28.6%
Space Separator
ValueCountFrequency (%)
430
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3189
84.8%
Common570
 
15.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e454
14.2%
a326
10.2%
m309
9.7%
t290
9.1%
o265
8.3%
n246
7.7%
c205
 
6.4%
s197
 
6.2%
i196
 
6.1%
u99
 
3.1%
Other values (15)602
18.9%
Common
ValueCountFrequency (%)
430
75.4%
,100
 
17.5%
/40
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3739
99.5%
None20
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e454
12.1%
430
11.5%
a326
 
8.7%
m309
 
8.3%
t290
 
7.8%
o265
 
7.1%
n246
 
6.6%
c205
 
5.5%
s197
 
5.3%
i196
 
5.2%
Other values (16)821
22.0%
None
ValueCountFrequency (%)
é19
95.0%
ó1
 
5.0%

racaagres
Categorical

HIGH CORRELATION
MISSING

Distinct20
Distinct (%)40.0%
Missing7
Missing (%)12.3%
Memory size584.0 B
Era um homem negro/pardo
Era um homem branco
Não sei dizer
Era um homem branco Era uma mulher branca Era um homem negro/pardo Era uma mulher negra/parda Era uma pessoa LGBTI negra Era uma pessoa LGBTI branca
Era um homem branco Era um homem negro/pardo
Other values (15)
17 

Length

Max length148
Median length99
Mean length53.44
Min length13

Characters and Unicode

Total characters2672
Distinct characters28
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)26.0%

Sample

1st rowEra um homem negro/pardo Não sei dizer
2nd rowEra um homem negro/pardo
3rd rowEra um homem branco Era um homem negro/pardo
4th rowEra um homem negro/pardo
5th rowEra um homem negro/pardo

Common Values

ValueCountFrequency (%)
Era um homem negro/pardo9
15.8%
Era um homem branco8
14.0%
Não sei dizer6
10.5%
Era um homem branco Era uma mulher branca Era um homem negro/pardo Era uma mulher negra/parda Era uma pessoa LGBTI negra Era uma pessoa LGBTI branca5
8.8%
Era um homem branco Era um homem negro/pardo5
8.8%
Era um homem branco Era uma mulher branca Era um homem negro/pardo Era uma mulher negra/parda2
 
3.5%
Era um homem branco Era uma mulher branca Era uma pessoa LGBTI branca2
 
3.5%
Era uma mulher branca Era um homem negro/pardo1
 
1.8%
Era uma mulher indígena1
 
1.8%
Era um homem negro/pardo Não sei dizer1
 
1.8%
Other values (10)10
17.5%
(Missing)7
12.3%

Length

2022-05-31T15:05:51.862765image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
era110
22.8%
um61
12.6%
homem61
12.6%
uma49
10.1%
negro/pardo30
 
6.2%
branco30
 
6.2%
branca28
 
5.8%
mulher27
 
5.6%
pessoa22
 
4.6%
lgbti22
 
4.6%
Other values (6)43
 
8.9%

Most occurring characters

ValueCountFrequency (%)
433
16.2%
a339
12.7%
r292
10.9%
m259
9.7%
o180
 
6.7%
e176
 
6.6%
u137
 
5.1%
n112
 
4.2%
E110
 
4.1%
h88
 
3.3%
Other values (18)546
20.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1972
73.8%
Space Separator433
 
16.2%
Uppercase Letter227
 
8.5%
Other Punctuation40
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a339
17.2%
r292
14.8%
m259
13.1%
o180
9.1%
e176
8.9%
u137
6.9%
n112
 
5.7%
h88
 
4.5%
p62
 
3.1%
c58
 
2.9%
Other values (9)269
13.6%
Uppercase Letter
ValueCountFrequency (%)
E110
48.5%
L22
 
9.7%
G22
 
9.7%
B22
 
9.7%
T22
 
9.7%
I22
 
9.7%
N7
 
3.1%
Space Separator
ValueCountFrequency (%)
433
100.0%
Other Punctuation
ValueCountFrequency (%)
/40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2199
82.3%
Common473
 
17.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a339
15.4%
r292
13.3%
m259
11.8%
o180
8.2%
e176
 
8.0%
u137
 
6.2%
n112
 
5.1%
E110
 
5.0%
h88
 
4.0%
p62
 
2.8%
Other values (16)444
20.2%
Common
ValueCountFrequency (%)
433
91.5%
/40
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII2663
99.7%
None9
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
433
16.3%
a339
12.7%
r292
11.0%
m259
9.7%
o180
 
6.8%
e176
 
6.6%
u137
 
5.1%
n112
 
4.2%
E110
 
4.1%
h88
 
3.3%
Other values (16)537
20.2%
None
ValueCountFrequency (%)
ã7
77.8%
í2
 
22.2%

abrdg
Categorical

HIGH CORRELATION

Distinct5
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size584.0 B
Não
14 
Sim, depois dos meus 18 anos.
13 
Sim, antes e depois dos meus 18 anos.
12 
Com frequência
11 
Sim, antes dos meus 18 anos.

Length

Max length37
Median length28
Mean length21.28070175
Min length3

Characters and Unicode

Total characters1213
Distinct characters25
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCom frequência
2nd rowNão
3rd rowSim, depois dos meus 18 anos.
4th rowSim, antes e depois dos meus 18 anos.
5th rowSim, depois dos meus 18 anos.

Common Values

ValueCountFrequency (%)
Não14
24.6%
Sim, depois dos meus 18 anos.13
22.8%
Sim, antes e depois dos meus 18 anos.12
21.1%
Com frequência11
19.3%
Sim, antes dos meus 18 anos.7
12.3%

Length

2022-05-31T15:05:51.990415image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:52.122066image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim32
12.7%
dos32
12.7%
meus32
12.7%
1832
12.7%
anos32
12.7%
depois25
9.9%
antes19
7.5%
não14
5.6%
e12
 
4.8%
com11
 
4.4%

Most occurring characters

ValueCountFrequency (%)
195
16.1%
s140
11.5%
o114
 
9.4%
e99
 
8.2%
m75
 
6.2%
i68
 
5.6%
n62
 
5.1%
a62
 
5.1%
d57
 
4.7%
u43
 
3.5%
Other values (15)298
24.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter833
68.7%
Space Separator195
 
16.1%
Other Punctuation64
 
5.3%
Decimal Number64
 
5.3%
Uppercase Letter57
 
4.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s140
16.8%
o114
13.7%
e99
11.9%
m75
9.0%
i68
8.2%
n62
7.4%
a62
7.4%
d57
6.8%
u43
 
5.2%
p25
 
3.0%
Other values (7)88
10.6%
Uppercase Letter
ValueCountFrequency (%)
S32
56.1%
N14
24.6%
C11
 
19.3%
Other Punctuation
ValueCountFrequency (%)
.32
50.0%
,32
50.0%
Decimal Number
ValueCountFrequency (%)
132
50.0%
832
50.0%
Space Separator
ValueCountFrequency (%)
195
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin890
73.4%
Common323
 
26.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
s140
15.7%
o114
12.8%
e99
11.1%
m75
8.4%
i68
7.6%
n62
7.0%
a62
7.0%
d57
6.4%
u43
 
4.8%
S32
 
3.6%
Other values (10)138
15.5%
Common
ValueCountFrequency (%)
195
60.4%
.32
 
9.9%
,32
 
9.9%
132
 
9.9%
832
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII1188
97.9%
None25
 
2.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
195
16.4%
s140
11.8%
o114
9.6%
e99
 
8.3%
m75
 
6.3%
i68
 
5.7%
n62
 
5.2%
a62
 
5.2%
d57
 
4.8%
u43
 
3.6%
Other values (13)273
23.0%
None
ValueCountFrequency (%)
ã14
56.0%
ê11
44.0%

ttoidgen
Categorical

HIGH CORRELATION
MISSING

Distinct6
Distinct (%)14.6%
Missing16
Missing (%)28.1%
Memory size584.0 B
NUNCA fui abordada de acordo com minha identidade de gênero
11 
SEMPRE fui abordada de acordo com minha identidade de gênero
ALGUMAS vezes fui abordada de acordo com minha identidade de gênero
POUCAS vezes fui abordada de acordo com minha identidade de gênero
Sim

Length

Max length67
Median length60
Mean length49.12195122
Min length3

Characters and Unicode

Total characters2014
Distinct characters33
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNUNCA fui abordada de acordo com minha identidade de gênero
2nd rowNUNCA fui abordada de acordo com minha identidade de gênero
3rd rowNUNCA fui abordada de acordo com minha identidade de gênero
4th rowALGUMAS vezes fui abordada de acordo com minha identidade de gênero
5th rowSEMPRE fui abordada de acordo com minha identidade de gênero

Common Values

ValueCountFrequency (%)
NUNCA fui abordada de acordo com minha identidade de gênero11
19.3%
SEMPRE fui abordada de acordo com minha identidade de gênero9
15.8%
ALGUMAS vezes fui abordada de acordo com minha identidade de gênero6
 
10.5%
POUCAS vezes fui abordada de acordo com minha identidade de gênero6
 
10.5%
Sim6
 
10.5%
Não3
 
5.3%
(Missing)16
28.1%

Length

2022-05-31T15:05:52.297553image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:52.442207image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
de64
18.8%
fui32
9.4%
abordada32
9.4%
acordo32
9.4%
com32
9.4%
minha32
9.4%
identidade32
9.4%
gênero32
9.4%
vezes12
 
3.5%
nunca11
 
3.2%
Other values (5)30
8.8%

Most occurring characters

ValueCountFrequency (%)
300
14.9%
d256
12.7%
a192
9.5%
e184
9.1%
o163
 
8.1%
i134
 
6.7%
n96
 
4.8%
r96
 
4.8%
m70
 
3.5%
c64
 
3.2%
Other values (23)459
22.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1518
75.4%
Space Separator300
 
14.9%
Uppercase Letter196
 
9.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
d256
16.9%
a192
12.6%
e184
12.1%
o163
10.7%
i134
8.8%
n96
 
6.3%
r96
 
6.3%
m70
 
4.6%
c64
 
4.2%
h32
 
2.1%
Other values (10)231
15.2%
Uppercase Letter
ValueCountFrequency (%)
A29
14.8%
S27
13.8%
N25
12.8%
U23
11.7%
E18
9.2%
C17
8.7%
M15
7.7%
P15
7.7%
R9
 
4.6%
L6
 
3.1%
Other values (2)12
6.1%
Space Separator
ValueCountFrequency (%)
300
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1714
85.1%
Common300
 
14.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
d256
14.9%
a192
11.2%
e184
10.7%
o163
 
9.5%
i134
 
7.8%
n96
 
5.6%
r96
 
5.6%
m70
 
4.1%
c64
 
3.7%
h32
 
1.9%
Other values (22)427
24.9%
Common
ValueCountFrequency (%)
300
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1979
98.3%
None35
 
1.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
300
15.2%
d256
12.9%
a192
9.7%
e184
9.3%
o163
 
8.2%
i134
 
6.8%
n96
 
4.9%
r96
 
4.9%
m70
 
3.5%
c64
 
3.2%
Other values (21)424
21.4%
None
ValueCountFrequency (%)
ê32
91.4%
ã3
 
8.6%

ameaidgen
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)7.1%
Missing15
Missing (%)26.3%
Memory size584.0 B
Sim
24 
Não
17 
Prefiro não responder
 
1

Length

Max length21
Median length3
Mean length3.428571429
Min length3

Characters and Unicode

Total characters144
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)2.4%

Sample

1st rowSim
2nd rowPrefiro não responder
3rd rowSim
4th rowNão
5th rowNão

Common Values

ValueCountFrequency (%)
Sim24
42.1%
Não17
29.8%
Prefiro não responder1
 
1.8%
(Missing)15
26.3%

Length

2022-05-31T15:05:52.609733image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:52.742405image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim24
54.5%
não18
40.9%
prefiro1
 
2.3%
responder1
 
2.3%

Most occurring characters

ValueCountFrequency (%)
i25
17.4%
S24
16.7%
m24
16.7%
o20
13.9%
ã18
12.5%
N17
11.8%
r4
 
2.8%
e3
 
2.1%
2
 
1.4%
n2
 
1.4%
Other values (5)5
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter100
69.4%
Uppercase Letter42
29.2%
Space Separator2
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i25
25.0%
m24
24.0%
o20
20.0%
ã18
18.0%
r4
 
4.0%
e3
 
3.0%
n2
 
2.0%
f1
 
1.0%
s1
 
1.0%
p1
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
S24
57.1%
N17
40.5%
P1
 
2.4%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin142
98.6%
Common2
 
1.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
i25
17.6%
S24
16.9%
m24
16.9%
o20
14.1%
ã18
12.7%
N17
12.0%
r4
 
2.8%
e3
 
2.1%
n2
 
1.4%
P1
 
0.7%
Other values (4)4
 
2.8%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII126
87.5%
None18
 
12.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i25
19.8%
S24
19.0%
m24
19.0%
o20
15.9%
N17
13.5%
r4
 
3.2%
e3
 
2.4%
2
 
1.6%
n2
 
1.6%
P1
 
0.8%
Other values (4)4
 
3.2%
None
ValueCountFrequency (%)
ã18
100.0%

delegc
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)4.7%
Missing14
Missing (%)24.6%
Memory size584.0 B
Não
27 
Sim
16 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters129
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão
2nd rowSim
3rd rowSim
4th rowNão
5th rowNão

Common Values

ValueCountFrequency (%)
Não27
47.4%
Sim16
28.1%
(Missing)14
24.6%

Length

2022-05-31T15:05:52.850075image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:52.963815image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não27
62.8%
sim16
37.2%

Most occurring characters

ValueCountFrequency (%)
N27
20.9%
ã27
20.9%
o27
20.9%
S16
12.4%
i16
12.4%
m16
12.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter86
66.7%
Uppercase Letter43
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
ã27
31.4%
o27
31.4%
i16
18.6%
m16
18.6%
Uppercase Letter
ValueCountFrequency (%)
N27
62.8%
S16
37.2%

Most occurring scripts

ValueCountFrequency (%)
Latin129
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N27
20.9%
ã27
20.9%
o27
20.9%
S16
12.4%
i16
12.4%
m16
12.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII102
79.1%
None27
 
20.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N27
26.5%
o27
26.5%
S16
15.7%
i16
15.7%
m16
15.7%
None
ValueCountFrequency (%)
ã27
100.0%

ondeplc
Categorical

HIGH CORRELATION
MISSING

Distinct17
Distinct (%)40.5%
Missing15
Missing (%)26.3%
Memory size584.0 B
Sim, na zona norte do Rio de Janeiro
12 
Sim, na zona sul do Rio de Janeiro
Sim, na zona oeste do Rio de Janeiro
Sim, na zona norte do Rio de Janeiro Sim, na zona oeste do Rio de Janeiro
Sim, na zona oeste do Rio de Janeiro Sim, no centro do Rio de Janeiro
Other values (12)
13 

Length

Max length216
Median length142
Mean length50.97619048
Min length2

Characters and Unicode

Total characters2141
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)26.2%

Sample

1st rowSim, na zona norte do Rio de Janeiro
2nd rowNão me lembro
3rd rowSim, na zona sul do Rio de Janeiro
4th rowSim, na zona norte do Rio de Janeiro
5th rowSim, na zona norte do Rio de Janeiro

Common Values

ValueCountFrequency (%)
Sim, na zona norte do Rio de Janeiro12
21.1%
Sim, na zona sul do Rio de Janeiro6
 
10.5%
Sim, na zona oeste do Rio de Janeiro6
 
10.5%
Sim, na zona norte do Rio de Janeiro Sim, na zona oeste do Rio de Janeiro3
 
5.3%
Sim, na zona oeste do Rio de Janeiro Sim, no centro do Rio de Janeiro2
 
3.5%
Não me lembro2
 
3.5%
DF1
 
1.8%
Curitiba, Dourados1
 
1.8%
Sim, na zona sul do Rio de Janeiro Sim, na zona norte do Rio de Janeiro Sim, na zona oeste do Rio de Janeiro Sim, no centro do Rio de Janeiro1
 
1.8%
Sim, na zona sul do Rio de Janeiro Sim, na zona norte do Rio de Janeiro Sim, fora da cidade do Rio de Janeiro Sim, no centro do Rio de Janeiro1
 
1.8%
Other values (7)7
12.3%
(Missing)15
26.3%

Length

2022-05-31T15:05:53.069527image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
sim59
12.5%
do59
12.5%
rio59
12.5%
de59
12.5%
janeiro59
12.5%
na47
9.9%
zona47
9.9%
norte21
 
4.4%
oeste13
 
2.7%
sul11
 
2.3%
Other values (12)39
8.2%

Most occurring characters

ValueCountFrequency (%)
431
20.1%
o284
13.3%
n190
8.9%
e185
8.6%
i183
8.5%
a167
 
7.8%
d131
 
6.1%
r96
 
4.5%
m63
 
2.9%
,60
 
2.8%
Other values (16)351
16.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1467
68.5%
Space Separator431
 
20.1%
Uppercase Letter183
 
8.5%
Other Punctuation60
 
2.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o284
19.4%
n190
13.0%
e185
12.6%
i183
12.5%
a167
11.4%
d131
8.9%
r96
 
6.5%
m63
 
4.3%
z47
 
3.2%
t45
 
3.1%
Other values (7)76
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
S59
32.2%
J59
32.2%
R59
32.2%
N2
 
1.1%
D2
 
1.1%
F1
 
0.5%
C1
 
0.5%
Space Separator
ValueCountFrequency (%)
431
100.0%
Other Punctuation
ValueCountFrequency (%)
,60
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1650
77.1%
Common491
 
22.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o284
17.2%
n190
11.5%
e185
11.2%
i183
11.1%
a167
10.1%
d131
7.9%
r96
 
5.8%
m63
 
3.8%
S59
 
3.6%
J59
 
3.6%
Other values (14)233
14.1%
Common
ValueCountFrequency (%)
431
87.8%
,60
 
12.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII2139
99.9%
None2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
431
20.1%
o284
13.3%
n190
8.9%
e185
8.6%
i183
8.6%
a167
 
7.8%
d131
 
6.1%
r96
 
4.5%
m63
 
2.9%
,60
 
2.8%
Other values (15)349
16.3%
None
ValueCountFrequency (%)
ã2
100.0%

acuspol
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)7.0%
Missing14
Missing (%)24.6%
Memory size584.0 B
Não
26 
Sim
15 
Prefiro não responder
 
2

Length

Max length21
Median length3
Mean length3.837209302
Min length3

Characters and Unicode

Total characters165
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowNão
3rd rowSim
4th rowNão
5th rowNão

Common Values

ValueCountFrequency (%)
Não26
45.6%
Sim15
26.3%
Prefiro não responder2
 
3.5%
(Missing)14
24.6%

Length

2022-05-31T15:05:53.184220image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:53.348740image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não28
59.6%
sim15
31.9%
prefiro2
 
4.3%
responder2
 
4.3%

Most occurring characters

ValueCountFrequency (%)
o32
19.4%
ã28
17.0%
N26
15.8%
i17
10.3%
S15
9.1%
m15
9.1%
r8
 
4.8%
e6
 
3.6%
4
 
2.4%
n4
 
2.4%
Other values (5)10
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter118
71.5%
Uppercase Letter43
 
26.1%
Space Separator4
 
2.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o32
27.1%
ã28
23.7%
i17
14.4%
m15
12.7%
r8
 
6.8%
e6
 
5.1%
n4
 
3.4%
f2
 
1.7%
s2
 
1.7%
p2
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
N26
60.5%
S15
34.9%
P2
 
4.7%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin161
97.6%
Common4
 
2.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
o32
19.9%
ã28
17.4%
N26
16.1%
i17
10.6%
S15
9.3%
m15
9.3%
r8
 
5.0%
e6
 
3.7%
n4
 
2.5%
P2
 
1.2%
Other values (4)8
 
5.0%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII137
83.0%
None28
 
17.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o32
23.4%
N26
19.0%
i17
12.4%
S15
10.9%
m15
10.9%
r8
 
5.8%
e6
 
4.4%
4
 
2.9%
n4
 
2.9%
P2
 
1.5%
Other values (4)8
 
5.8%
None
ValueCountFrequency (%)
ã28
100.0%

violplc
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)7.1%
Missing15
Missing (%)26.3%
Memory size584.0 B
Sim
25 
Não
16 
Prefiro não responder
 
1

Length

Max length21
Median length3
Mean length3.428571429
Min length3

Characters and Unicode

Total characters144
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)2.4%

Sample

1st rowSim
2nd rowNão
3rd rowSim
4th rowNão
5th rowNão

Common Values

ValueCountFrequency (%)
Sim25
43.9%
Não16
28.1%
Prefiro não responder1
 
1.8%
(Missing)15
26.3%

Length

2022-05-31T15:05:53.491359image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:53.619057image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim25
56.8%
não17
38.6%
prefiro1
 
2.3%
responder1
 
2.3%

Most occurring characters

ValueCountFrequency (%)
i26
18.1%
S25
17.4%
m25
17.4%
o19
13.2%
ã17
11.8%
N16
11.1%
r4
 
2.8%
e3
 
2.1%
2
 
1.4%
n2
 
1.4%
Other values (5)5
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter100
69.4%
Uppercase Letter42
29.2%
Space Separator2
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i26
26.0%
m25
25.0%
o19
19.0%
ã17
17.0%
r4
 
4.0%
e3
 
3.0%
n2
 
2.0%
f1
 
1.0%
s1
 
1.0%
p1
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
S25
59.5%
N16
38.1%
P1
 
2.4%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin142
98.6%
Common2
 
1.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
i26
18.3%
S25
17.6%
m25
17.6%
o19
13.4%
ã17
12.0%
N16
11.3%
r4
 
2.8%
e3
 
2.1%
n2
 
1.4%
P1
 
0.7%
Other values (4)4
 
2.8%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII127
88.2%
None17
 
11.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i26
20.5%
S25
19.7%
m25
19.7%
o19
15.0%
N16
12.6%
r4
 
3.1%
e3
 
2.4%
2
 
1.6%
n2
 
1.6%
P1
 
0.8%
Other values (4)4
 
3.1%
None
ValueCountFrequency (%)
ã17
100.0%

extorsplc
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size584.0 B
Não
33 
Sim
22 
Prefiro não responder
 
2

Length

Max length21
Median length3
Mean length3.631578947
Min length3

Characters and Unicode

Total characters207
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão
2nd rowNão
3rd rowNão
4th rowSim
5th rowNão

Common Values

ValueCountFrequency (%)
Não33
57.9%
Sim22
38.6%
Prefiro não responder2
 
3.5%

Length

2022-05-31T15:05:53.730720image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:53.858376image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não35
57.4%
sim22
36.1%
prefiro2
 
3.3%
responder2
 
3.3%

Most occurring characters

ValueCountFrequency (%)
o39
18.8%
ã35
16.9%
N33
15.9%
i24
11.6%
S22
10.6%
m22
10.6%
r8
 
3.9%
e6
 
2.9%
4
 
1.9%
n4
 
1.9%
Other values (5)10
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter146
70.5%
Uppercase Letter57
 
27.5%
Space Separator4
 
1.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o39
26.7%
ã35
24.0%
i24
16.4%
m22
15.1%
r8
 
5.5%
e6
 
4.1%
n4
 
2.7%
f2
 
1.4%
s2
 
1.4%
p2
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
N33
57.9%
S22
38.6%
P2
 
3.5%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin203
98.1%
Common4
 
1.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o39
19.2%
ã35
17.2%
N33
16.3%
i24
11.8%
S22
10.8%
m22
10.8%
r8
 
3.9%
e6
 
3.0%
n4
 
2.0%
P2
 
1.0%
Other values (4)8
 
3.9%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII172
83.1%
None35
 
16.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o39
22.7%
N33
19.2%
i24
14.0%
S22
12.8%
m22
12.8%
r8
 
4.7%
e6
 
3.5%
4
 
2.3%
n4
 
2.3%
P2
 
1.2%
Other values (4)8
 
4.7%
None
ValueCountFrequency (%)
ã35
100.0%

foraplc
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)3.6%
Missing1
Missing (%)1.8%
Memory size584.0 B
Não
40 
Sim
16 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters168
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowNão
3rd rowNão
4th rowNão
5th rowNão

Common Values

ValueCountFrequency (%)
Não40
70.2%
Sim16
 
28.1%
(Missing)1
 
1.8%

Length

2022-05-31T15:05:53.963096image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:54.066860image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não40
71.4%
sim16
 
28.6%

Most occurring characters

ValueCountFrequency (%)
N40
23.8%
ã40
23.8%
o40
23.8%
S16
 
9.5%
i16
 
9.5%
m16
 
9.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter112
66.7%
Uppercase Letter56
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
ã40
35.7%
o40
35.7%
i16
 
14.3%
m16
 
14.3%
Uppercase Letter
ValueCountFrequency (%)
N40
71.4%
S16
 
28.6%

Most occurring scripts

ValueCountFrequency (%)
Latin168
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N40
23.8%
ã40
23.8%
o40
23.8%
S16
 
9.5%
i16
 
9.5%
m16
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII128
76.2%
None40
 
23.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N40
31.2%
o40
31.2%
S16
 
12.5%
i16
 
12.5%
m16
 
12.5%
None
ValueCountFrequency (%)
ã40
100.0%

moraplc
Categorical

HIGH CORRELATION

Distinct4
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size584.0 B
Não, nunca aconteceu
23 
Sim, várias vezes
18 
Sim, poucas vezes
11 
Sim, com frequência

Length

Max length20
Median length17
Mean length18.38596491
Min length17

Characters and Unicode

Total characters1048
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão, nunca aconteceu
2nd rowNão, nunca aconteceu
3rd rowNão, nunca aconteceu
4th rowNão, nunca aconteceu
5th rowNão, nunca aconteceu

Common Values

ValueCountFrequency (%)
Não, nunca aconteceu23
40.4%
Sim, várias vezes18
31.6%
Sim, poucas vezes11
19.3%
Sim, com frequência5
 
8.8%

Length

2022-05-31T15:05:54.168584image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:54.313201image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim34
19.9%
vezes29
17.0%
não23
13.5%
nunca23
13.5%
aconteceu23
13.5%
várias18
10.5%
poucas11
 
6.4%
com5
 
2.9%
frequência5
 
2.9%

Most occurring characters

ValueCountFrequency (%)
114
 
10.9%
e109
 
10.4%
c90
 
8.6%
a80
 
7.6%
n74
 
7.1%
o62
 
5.9%
u62
 
5.9%
s58
 
5.5%
,57
 
5.4%
i57
 
5.4%
Other values (13)285
27.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter820
78.2%
Space Separator114
 
10.9%
Other Punctuation57
 
5.4%
Uppercase Letter57
 
5.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e109
13.3%
c90
11.0%
a80
9.8%
n74
9.0%
o62
7.6%
u62
7.6%
s58
7.1%
i57
7.0%
v47
 
5.7%
m39
 
4.8%
Other values (9)142
17.3%
Uppercase Letter
ValueCountFrequency (%)
S34
59.6%
N23
40.4%
Space Separator
ValueCountFrequency (%)
114
100.0%
Other Punctuation
ValueCountFrequency (%)
,57
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin877
83.7%
Common171
 
16.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e109
12.4%
c90
10.3%
a80
9.1%
n74
 
8.4%
o62
 
7.1%
u62
 
7.1%
s58
 
6.6%
i57
 
6.5%
v47
 
5.4%
m39
 
4.4%
Other values (11)199
22.7%
Common
ValueCountFrequency (%)
114
66.7%
,57
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII1002
95.6%
None46
 
4.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
114
11.4%
e109
10.9%
c90
 
9.0%
a80
 
8.0%
n74
 
7.4%
o62
 
6.2%
u62
 
6.2%
s58
 
5.8%
,57
 
5.7%
i57
 
5.7%
Other values (10)239
23.9%
None
ValueCountFrequency (%)
ã23
50.0%
á18
39.1%
ê5
 
10.9%

invcsplc
Categorical

HIGH CORRELATION

Distinct4
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size584.0 B
Não, nunca aconteceu
24 
Sim, poucas vezes
15 
Sim, várias vezes
14 
Sim, com frequência

Length

Max length20
Median length17
Mean length18.40350877
Min length17

Characters and Unicode

Total characters1049
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão, nunca aconteceu
2nd rowNão, nunca aconteceu
3rd rowSim, várias vezes
4th rowSim, com frequência
5th rowNão, nunca aconteceu

Common Values

ValueCountFrequency (%)
Não, nunca aconteceu24
42.1%
Sim, poucas vezes15
26.3%
Sim, várias vezes14
24.6%
Sim, com frequência4
 
7.0%

Length

2022-05-31T15:05:54.487734image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:54.634341image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim33
19.3%
vezes29
17.0%
não24
14.0%
nunca24
14.0%
aconteceu24
14.0%
poucas15
8.8%
várias14
8.2%
com4
 
2.3%
frequência4
 
2.3%

Most occurring characters

ValueCountFrequency (%)
114
10.9%
e110
10.5%
c95
 
9.1%
a81
 
7.7%
n76
 
7.2%
o67
 
6.4%
u67
 
6.4%
s58
 
5.5%
,57
 
5.4%
i51
 
4.9%
Other values (13)273
26.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter821
78.3%
Space Separator114
 
10.9%
Other Punctuation57
 
5.4%
Uppercase Letter57
 
5.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e110
13.4%
c95
11.6%
a81
9.9%
n76
9.3%
o67
8.2%
u67
8.2%
s58
7.1%
i51
 
6.2%
v43
 
5.2%
m37
 
4.5%
Other values (9)136
16.6%
Uppercase Letter
ValueCountFrequency (%)
S33
57.9%
N24
42.1%
Space Separator
ValueCountFrequency (%)
114
100.0%
Other Punctuation
ValueCountFrequency (%)
,57
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin878
83.7%
Common171
 
16.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e110
12.5%
c95
10.8%
a81
9.2%
n76
 
8.7%
o67
 
7.6%
u67
 
7.6%
s58
 
6.6%
i51
 
5.8%
v43
 
4.9%
m37
 
4.2%
Other values (11)193
22.0%
Common
ValueCountFrequency (%)
114
66.7%
,57
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII1007
96.0%
None42
 
4.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
114
11.3%
e110
10.9%
c95
9.4%
a81
 
8.0%
n76
 
7.5%
o67
 
6.7%
u67
 
6.7%
s58
 
5.8%
,57
 
5.7%
i51
 
5.1%
Other values (10)231
22.9%
None
ValueCountFrequency (%)
ã24
57.1%
á14
33.3%
ê4
 
9.5%

vldenunplc
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)5.4%
Missing1
Missing (%)1.8%
Memory size584.0 B
Não
47 
Sim
Prefiro não responder
 
4

Length

Max length21
Median length3
Mean length4.285714286
Min length3

Characters and Unicode

Total characters240
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão
2nd rowNão
3rd rowNão
4th rowSim
5th rowNão

Common Values

ValueCountFrequency (%)
Não47
82.5%
Sim5
 
8.8%
Prefiro não responder4
 
7.0%
(Missing)1
 
1.8%

Length

2022-05-31T15:05:54.757021image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:54.872705image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não51
79.7%
sim5
 
7.8%
prefiro4
 
6.2%
responder4
 
6.2%

Most occurring characters

ValueCountFrequency (%)
o59
24.6%
ã51
21.2%
N47
19.6%
r16
 
6.7%
e12
 
5.0%
i9
 
3.8%
8
 
3.3%
n8
 
3.3%
S5
 
2.1%
m5
 
2.1%
Other values (5)20
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter176
73.3%
Uppercase Letter56
 
23.3%
Space Separator8
 
3.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o59
33.5%
ã51
29.0%
r16
 
9.1%
e12
 
6.8%
i9
 
5.1%
n8
 
4.5%
m5
 
2.8%
f4
 
2.3%
s4
 
2.3%
p4
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
N47
83.9%
S5
 
8.9%
P4
 
7.1%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin232
96.7%
Common8
 
3.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o59
25.4%
ã51
22.0%
N47
20.3%
r16
 
6.9%
e12
 
5.2%
i9
 
3.9%
n8
 
3.4%
S5
 
2.2%
m5
 
2.2%
P4
 
1.7%
Other values (4)16
 
6.9%
Common
ValueCountFrequency (%)
8
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII189
78.8%
None51
 
21.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o59
31.2%
N47
24.9%
r16
 
8.5%
e12
 
6.3%
i9
 
4.8%
8
 
4.2%
n8
 
4.2%
S5
 
2.6%
m5
 
2.6%
P4
 
2.1%
Other values (4)16
 
8.5%
None
ValueCountFrequency (%)
ã51
100.0%

possuireli
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size584.0 B
Sim
39 
Não
18 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters171
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão
2nd rowNão
3rd rowNão
4th rowNão
5th rowNão

Common Values

ValueCountFrequency (%)
Sim39
68.4%
Não18
31.6%

Length

2022-05-31T15:05:54.983407image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:55.092120image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim39
68.4%
não18
31.6%

Most occurring characters

ValueCountFrequency (%)
S39
22.8%
i39
22.8%
m39
22.8%
N18
10.5%
ã18
10.5%
o18
10.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter114
66.7%
Uppercase Letter57
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i39
34.2%
m39
34.2%
ã18
15.8%
o18
15.8%
Uppercase Letter
ValueCountFrequency (%)
S39
68.4%
N18
31.6%

Most occurring scripts

ValueCountFrequency (%)
Latin171
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S39
22.8%
i39
22.8%
m39
22.8%
N18
10.5%
ã18
10.5%
o18
10.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII153
89.5%
None18
 
10.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S39
25.5%
i39
25.5%
m39
25.5%
N18
11.8%
o18
11.8%
None
ValueCountFrequency (%)
ã18
100.0%

tprelig
Categorical

HIGH CORRELATION
MISSING

Distinct27
Distinct (%)73.0%
Missing20
Missing (%)35.1%
Memory size584.0 B
Católica
Candomblé
Espírita
Umbanda
 
2
Espírita
 
2
Other values (22)
23 

Length

Max length39
Median length31
Mean length11.40540541
Min length4

Characters and Unicode

Total characters422
Distinct characters34
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)56.8%

Sample

1st rowUmbandistas
2nd rowCatólica
3rd rowCatólica
4th rowCatólica
5th rowCandomblé

Common Values

ValueCountFrequency (%)
Católica 4
 
7.0%
Candomblé3
 
5.3%
Espírita3
 
5.3%
Umbanda 2
 
3.5%
Espírita 2
 
3.5%
Candomblé 2
 
3.5%
Católica1
 
1.8%
candomblé 1
 
1.8%
Acredita em Deus, mas não tem religiosa1
 
1.8%
Crença em Deus1
 
1.8%
Other values (17)17
29.8%
(Missing)20
35.1%

Length

2022-05-31T15:05:55.213753image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
espírita6
 
10.9%
candomblé6
 
10.9%
católica5
 
9.1%
deus4
 
7.3%
umbanda3
 
5.5%
em3
 
5.5%
católico2
 
3.6%
pra2
 
3.6%
uma1
 
1.8%
entidade1
 
1.8%
Other values (22)22
40.0%

Most occurring characters

ValueCountFrequency (%)
a56
 
13.3%
33
 
7.8%
i27
 
6.4%
t25
 
5.9%
m24
 
5.7%
e23
 
5.5%
l20
 
4.7%
s19
 
4.5%
C19
 
4.5%
d18
 
4.3%
Other values (24)158
37.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter345
81.8%
Uppercase Letter36
 
8.5%
Space Separator33
 
7.8%
Other Punctuation8
 
1.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a56
16.2%
i27
 
7.8%
t25
 
7.2%
m24
 
7.0%
e23
 
6.7%
l20
 
5.8%
s19
 
5.5%
d18
 
5.2%
o17
 
4.9%
n17
 
4.9%
Other values (13)99
28.7%
Uppercase Letter
ValueCountFrequency (%)
C19
52.8%
E6
 
16.7%
U4
 
11.1%
D4
 
11.1%
A1
 
2.8%
V1
 
2.8%
M1
 
2.8%
Other Punctuation
ValueCountFrequency (%)
.4
50.0%
,2
25.0%
/2
25.0%
Space Separator
ValueCountFrequency (%)
33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin381
90.3%
Common41
 
9.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a56
14.7%
i27
 
7.1%
t25
 
6.6%
m24
 
6.3%
e23
 
6.0%
l20
 
5.2%
s19
 
5.0%
C19
 
5.0%
d18
 
4.7%
o17
 
4.5%
Other values (20)133
34.9%
Common
ValueCountFrequency (%)
33
80.5%
.4
 
9.8%
,2
 
4.9%
/2
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII397
94.1%
None25
 
5.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a56
14.1%
33
 
8.3%
i27
 
6.8%
t25
 
6.3%
m24
 
6.0%
e23
 
5.8%
l20
 
5.0%
s19
 
4.8%
C19
 
4.8%
d18
 
4.5%
Other values (19)133
33.5%
None
ValueCountFrequency (%)
ó8
32.0%
í7
28.0%
é7
28.0%
ã2
 
8.0%
ç1
 
4.0%

criareli
Categorical

HIGH CORRELATION
MISSING

Distinct28
Distinct (%)50.0%
Missing1
Missing (%)1.8%
Memory size584.0 B
Não fui criada em nenhuma crença religiosa
13 
Evangélica
Católica
Evangélica
Catolicismo
Other values (23)
26 

Length

Max length42
Median length25
Mean length18.03571429
Min length5

Characters and Unicode

Total characters1010
Distinct characters46
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)37.5%

Sample

1st rowCristã
2nd rowEvangélica
3rd rowMinha umbanda de axé ❤
4th rowWicca
5th rowCatólica

Common Values

ValueCountFrequency (%)
Não fui criada em nenhuma crença religiosa13
22.8%
Evangélica5
 
8.8%
Católica 5
 
8.8%
Evangélica 4
 
7.0%
Catolicismo3
 
5.3%
Católica3
 
5.3%
Cristã2
 
3.5%
Igreja católica 1
 
1.8%
ESPÍRITA 1
 
1.8%
Católico 1
 
1.8%
Other values (18)18
31.6%

Length

2022-05-31T15:05:55.367344image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
não13
8.9%
criada13
8.9%
em13
8.9%
nenhuma13
8.9%
crença13
8.9%
religiosa13
8.9%
fui13
8.9%
evangélica12
8.2%
católica12
8.2%
igreja3
 
2.1%
Other values (18)28
19.2%

Most occurring characters

ValueCountFrequency (%)
a147
14.6%
108
 
10.7%
i93
 
9.2%
c63
 
6.2%
e62
 
6.1%
n61
 
6.0%
l48
 
4.8%
r47
 
4.7%
m41
 
4.1%
o37
 
3.7%
Other values (36)303
30.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter839
83.1%
Space Separator108
 
10.7%
Uppercase Letter59
 
5.8%
Other Symbol1
 
0.1%
Other Punctuation1
 
0.1%
Open Punctuation1
 
0.1%
Close Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a147
17.5%
i93
11.1%
c63
 
7.5%
e62
 
7.4%
n61
 
7.3%
l48
 
5.7%
r47
 
5.6%
m41
 
4.9%
o37
 
4.4%
u29
 
3.5%
Other values (16)211
25.1%
Uppercase Letter
ValueCountFrequency (%)
C16
27.1%
N13
22.0%
E11
18.6%
I4
 
6.8%
U3
 
5.1%
M2
 
3.4%
F2
 
3.4%
S1
 
1.7%
B1
 
1.7%
P1
 
1.7%
Other values (5)5
 
8.5%
Space Separator
ValueCountFrequency (%)
108
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%
Other Punctuation
ValueCountFrequency (%)
;1
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin898
88.9%
Common112
 
11.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a147
16.4%
i93
 
10.4%
c63
 
7.0%
e62
 
6.9%
n61
 
6.8%
l48
 
5.3%
r47
 
5.2%
m41
 
4.6%
o37
 
4.1%
u29
 
3.2%
Other values (31)270
30.1%
Common
ValueCountFrequency (%)
108
96.4%
1
 
0.9%
;1
 
0.9%
(1
 
0.9%
)1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII946
93.7%
None63
 
6.2%
Dingbats1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a147
15.5%
108
11.4%
i93
 
9.8%
c63
 
6.7%
e62
 
6.6%
n61
 
6.4%
l48
 
5.1%
r47
 
5.0%
m41
 
4.3%
o37
 
3.9%
Other values (29)239
25.3%
None
ValueCountFrequency (%)
é16
25.4%
ã16
25.4%
ó13
20.6%
ç13
20.6%
í4
 
6.3%
Í1
 
1.6%
Dingbats
ValueCountFrequency (%)
1
100.0%

proxreli
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size584.0 B
Praticante
23 
Nada próxima
17 
Pouco próxima
17 

Length

Max length13
Median length12
Mean length11.49122807
Min length10

Characters and Unicode

Total characters655
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNada próxima
2nd rowNada próxima
3rd rowPraticante
4th rowPouco próxima
5th rowNada próxima

Common Values

ValueCountFrequency (%)
Praticante23
40.4%
Nada próxima17
29.8%
Pouco próxima17
29.8%

Length

2022-05-31T15:05:55.543493image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:55.770848image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
próxima34
37.4%
praticante23
25.3%
nada17
18.7%
pouco17
18.7%

Most occurring characters

ValueCountFrequency (%)
a114
17.4%
i57
 
8.7%
r57
 
8.7%
t46
 
7.0%
P40
 
6.1%
c40
 
6.1%
m34
 
5.2%
o34
 
5.2%
34
 
5.2%
p34
 
5.2%
Other values (7)165
25.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter564
86.1%
Uppercase Letter57
 
8.7%
Space Separator34
 
5.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a114
20.2%
i57
10.1%
r57
10.1%
t46
8.2%
c40
 
7.1%
m34
 
6.0%
o34
 
6.0%
p34
 
6.0%
ó34
 
6.0%
x34
 
6.0%
Other values (4)80
14.2%
Uppercase Letter
ValueCountFrequency (%)
P40
70.2%
N17
29.8%
Space Separator
ValueCountFrequency (%)
34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin621
94.8%
Common34
 
5.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a114
18.4%
i57
9.2%
r57
9.2%
t46
 
7.4%
P40
 
6.4%
c40
 
6.4%
m34
 
5.5%
o34
 
5.5%
p34
 
5.5%
ó34
 
5.5%
Other values (6)131
21.1%
Common
ValueCountFrequency (%)
34
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII621
94.8%
None34
 
5.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a114
18.4%
i57
9.2%
r57
9.2%
t46
 
7.4%
P40
 
6.4%
c40
 
6.4%
m34
 
5.5%
o34
 
5.5%
34
 
5.5%
p34
 
5.5%
Other values (6)131
21.1%
None
ValueCountFrequency (%)
ó34
100.0%

opressreli
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size584.0 B
Sim
34 
Não
20 
Não sei
 
3

Length

Max length7
Median length3
Mean length3.210526316
Min length3

Characters and Unicode

Total characters183
Distinct characters9
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowSim
3rd rowNão
4th rowNão
5th rowNão

Common Values

ValueCountFrequency (%)
Sim34
59.6%
Não20
35.1%
Não sei3
 
5.3%

Length

2022-05-31T15:05:56.185738image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:56.320377image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim34
56.7%
não23
38.3%
sei3
 
5.0%

Most occurring characters

ValueCountFrequency (%)
i37
20.2%
S34
18.6%
m34
18.6%
N23
12.6%
ã23
12.6%
o23
12.6%
3
 
1.6%
s3
 
1.6%
e3
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter123
67.2%
Uppercase Letter57
31.1%
Space Separator3
 
1.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i37
30.1%
m34
27.6%
ã23
18.7%
o23
18.7%
s3
 
2.4%
e3
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
S34
59.6%
N23
40.4%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin180
98.4%
Common3
 
1.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
i37
20.6%
S34
18.9%
m34
18.9%
N23
12.8%
ã23
12.8%
o23
12.8%
s3
 
1.7%
e3
 
1.7%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII160
87.4%
None23
 
12.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i37
23.1%
S34
21.2%
m34
21.2%
N23
14.4%
o23
14.4%
3
 
1.9%
s3
 
1.9%
e3
 
1.9%
None
ValueCountFrequency (%)
ã23
100.0%

violreli
Categorical

HIGH CORRELATION

Distinct4
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size584.0 B
Não
29 
Sim
23 
Não sei
Prefiro não responder
 
2

Length

Max length21
Median length3
Mean length3.842105263
Min length3

Characters and Unicode

Total characters219
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowNão
3rd rowPrefiro não responder
4th rowNão
5th rowNão

Common Values

ValueCountFrequency (%)
Não29
50.9%
Sim23
40.4%
Não sei3
 
5.3%
Prefiro não responder2
 
3.5%

Length

2022-05-31T15:05:56.436068image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:56.591652image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não34
53.1%
sim23
35.9%
sei3
 
4.7%
prefiro2
 
3.1%
responder2
 
3.1%

Most occurring characters

ValueCountFrequency (%)
o38
17.4%
ã34
15.5%
N32
14.6%
i28
12.8%
S23
10.5%
m23
10.5%
e9
 
4.1%
r8
 
3.7%
7
 
3.2%
s5
 
2.3%
Other values (5)12
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter155
70.8%
Uppercase Letter57
 
26.0%
Space Separator7
 
3.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o38
24.5%
ã34
21.9%
i28
18.1%
m23
14.8%
e9
 
5.8%
r8
 
5.2%
s5
 
3.2%
n4
 
2.6%
f2
 
1.3%
p2
 
1.3%
Uppercase Letter
ValueCountFrequency (%)
N32
56.1%
S23
40.4%
P2
 
3.5%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin212
96.8%
Common7
 
3.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
o38
17.9%
ã34
16.0%
N32
15.1%
i28
13.2%
S23
10.8%
m23
10.8%
e9
 
4.2%
r8
 
3.8%
s5
 
2.4%
n4
 
1.9%
Other values (4)8
 
3.8%
Common
ValueCountFrequency (%)
7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII185
84.5%
None34
 
15.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o38
20.5%
N32
17.3%
i28
15.1%
S23
12.4%
m23
12.4%
e9
 
4.9%
r8
 
4.3%
7
 
3.8%
s5
 
2.7%
n4
 
2.2%
Other values (4)8
 
4.3%
None
ValueCountFrequency (%)
ã34
100.0%

orisexreli
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)3.6%
Missing1
Missing (%)1.8%
Memory size584.0 B
Não
32 
Sim
24 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters168
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowNão
3rd rowNão
4th rowNão
5th rowSim

Common Values

ValueCountFrequency (%)
Não32
56.1%
Sim24
42.1%
(Missing)1
 
1.8%

Length

2022-05-31T15:05:56.722302image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:56.840985image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não32
57.1%
sim24
42.9%

Most occurring characters

ValueCountFrequency (%)
N32
19.0%
ã32
19.0%
o32
19.0%
S24
14.3%
i24
14.3%
m24
14.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter112
66.7%
Uppercase Letter56
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
ã32
28.6%
o32
28.6%
i24
21.4%
m24
21.4%
Uppercase Letter
ValueCountFrequency (%)
N32
57.1%
S24
42.9%

Most occurring scripts

ValueCountFrequency (%)
Latin168
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N32
19.0%
ã32
19.0%
o32
19.0%
S24
14.3%
i24
14.3%
m24
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII136
81.0%
None32
 
19.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N32
23.5%
o32
23.5%
S24
17.6%
i24
17.6%
m24
17.6%
None
ValueCountFrequency (%)
ã32
100.0%

desacrerreli
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size584.0 B
Sim
34 
Não
23 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters171
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowNão
3rd rowNão
4th rowNão
5th rowSim

Common Values

ValueCountFrequency (%)
Sim34
59.6%
Não23
40.4%

Length

2022-05-31T15:05:56.943710image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:57.072366image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim34
59.6%
não23
40.4%

Most occurring characters

ValueCountFrequency (%)
S34
19.9%
i34
19.9%
m34
19.9%
N23
13.5%
ã23
13.5%
o23
13.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter114
66.7%
Uppercase Letter57
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i34
29.8%
m34
29.8%
ã23
20.2%
o23
20.2%
Uppercase Letter
ValueCountFrequency (%)
S34
59.6%
N23
40.4%

Most occurring scripts

ValueCountFrequency (%)
Latin171
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S34
19.9%
i34
19.9%
m34
19.9%
N23
13.5%
ã23
13.5%
o23
13.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII148
86.5%
None23
 
13.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S34
23.0%
i34
23.0%
m34
23.0%
N23
15.5%
o23
15.5%
None
ValueCountFrequency (%)
ã23
100.0%

forcareli
Categorical

HIGH CORRELATION
MISSING

Distinct6
Distinct (%)10.7%
Missing1
Missing (%)1.8%
Memory size584.0 B
Não
28 
Sim, na minha igreja ou ordem religiosa
12 
Sim, dentro da minha casa ou de parentes
Não sei
Sim, na escola
 
2

Length

Max length40
Median length39.5
Mean length16.76785714
Min length3

Characters and Unicode

Total characters939
Distinct characters22
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim, dentro da minha casa ou de parentes
2nd rowNão
3rd rowSim, na escola
4th rowNão
5th rowNão sei

Common Values

ValueCountFrequency (%)
Não28
49.1%
Sim, na minha igreja ou ordem religiosa12
21.1%
Sim, dentro da minha casa ou de parentes7
 
12.3%
Não sei5
 
8.8%
Sim, na escola2
 
3.5%
Sim, na casa de amigos2
 
3.5%
(Missing)1
 
1.8%

Length

2022-05-31T15:05:57.202019image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:57.431405image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não33
17.0%
sim23
11.9%
minha19
9.8%
ou19
9.8%
na16
8.2%
igreja12
 
6.2%
ordem12
 
6.2%
religiosa12
 
6.2%
casa9
 
4.6%
de9
 
4.6%
Other values (6)30
15.5%

Most occurring characters

ValueCountFrequency (%)
138
14.7%
a95
10.1%
o87
 
9.3%
i85
 
9.1%
e73
 
7.8%
m56
 
6.0%
r50
 
5.3%
n49
 
5.2%
s37
 
3.9%
d35
 
3.7%
Other values (12)234
24.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter722
76.9%
Space Separator138
 
14.7%
Uppercase Letter56
 
6.0%
Other Punctuation23
 
2.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a95
13.2%
o87
12.0%
i85
11.8%
e73
10.1%
m56
7.8%
r50
6.9%
n49
6.8%
s37
 
5.1%
d35
 
4.8%
ã33
 
4.6%
Other values (8)122
16.9%
Uppercase Letter
ValueCountFrequency (%)
N33
58.9%
S23
41.1%
Space Separator
ValueCountFrequency (%)
138
100.0%
Other Punctuation
ValueCountFrequency (%)
,23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin778
82.9%
Common161
 
17.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a95
12.2%
o87
11.2%
i85
10.9%
e73
9.4%
m56
 
7.2%
r50
 
6.4%
n49
 
6.3%
s37
 
4.8%
d35
 
4.5%
N33
 
4.2%
Other values (10)178
22.9%
Common
ValueCountFrequency (%)
138
85.7%
,23
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII906
96.5%
None33
 
3.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
138
15.2%
a95
10.5%
o87
9.6%
i85
9.4%
e73
 
8.1%
m56
 
6.2%
r50
 
5.5%
n49
 
5.4%
s37
 
4.1%
d35
 
3.9%
Other values (11)201
22.2%
None
ValueCountFrequency (%)
ã33
100.0%

igrevive
Categorical

HIGH CORRELATION

Distinct4
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size584.0 B
Sim
24 
Não
16 
Não sei
14 
Prefiro não responder

Length

Max length21
Median length3
Mean length4.929824561
Min length3

Characters and Unicode

Total characters281
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowNão
3rd rowNão sei
4th rowNão
5th rowNão sei

Common Values

ValueCountFrequency (%)
Sim24
42.1%
Não16
28.1%
Não sei14
24.6%
Prefiro não responder3
 
5.3%

Length

2022-05-31T15:05:57.689715image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:57.900152image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não33
42.9%
sim24
31.2%
sei14
18.2%
prefiro3
 
3.9%
responder3
 
3.9%

Most occurring characters

ValueCountFrequency (%)
i41
14.6%
o39
13.9%
ã33
11.7%
N30
10.7%
S24
8.5%
m24
8.5%
e23
8.2%
20
7.1%
s17
6.0%
r12
 
4.3%
Other values (5)18
6.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter204
72.6%
Uppercase Letter57
 
20.3%
Space Separator20
 
7.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i41
20.1%
o39
19.1%
ã33
16.2%
m24
11.8%
e23
11.3%
s17
8.3%
r12
 
5.9%
n6
 
2.9%
f3
 
1.5%
p3
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
N30
52.6%
S24
42.1%
P3
 
5.3%
Space Separator
ValueCountFrequency (%)
20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin261
92.9%
Common20
 
7.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
i41
15.7%
o39
14.9%
ã33
12.6%
N30
11.5%
S24
9.2%
m24
9.2%
e23
8.8%
s17
6.5%
r12
 
4.6%
n6
 
2.3%
Other values (4)12
 
4.6%
Common
ValueCountFrequency (%)
20
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII248
88.3%
None33
 
11.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i41
16.5%
o39
15.7%
N30
12.1%
S24
9.7%
m24
9.7%
e23
9.3%
20
8.1%
s17
6.9%
r12
 
4.8%
n6
 
2.4%
Other values (4)12
 
4.8%
None
ValueCountFrequency (%)
ã33
100.0%

acesnet
Categorical

HIGH CORRELATION

Distinct34
Distinct (%)59.6%
Missing0
Missing (%)0.0%
Memory size584.0 B
Tenho um plano residencial de internet
Internet celular pós-paga (franquia de dados + aplicativos) Tenho um plano residencial de internet
Celular pré-pago (dados limitados + aplicativos) Tenho um plano residencial de internet
Celular pré-pago (dados limitados + aplicativos)
Celular pré-pago (dados limitados + aplicativos) Por pontos de wi-fi abertos pela cidade (internet provida por governo/empresas)
 
3
Other values (29)
34 

Length

Max length297
Median length204
Mean length112.1578947
Min length30

Characters and Unicode

Total characters6393
Distinct characters41
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)43.9%

Sample

1st rowTenho um plano residencial de internet
2nd rowTenho um plano residencial de internet
3rd rowInternet por redes de vizinhos
4th rowCelular pré-pago (dados limitados + aplicativos)
5th rowInternet por redes de vizinhos Por pontos de wi-fi abertos pela cidade (internet provida por governo/empresas)

Common Values

ValueCountFrequency (%)
Tenho um plano residencial de internet6
 
10.5%
Internet celular pós-paga (franquia de dados + aplicativos) Tenho um plano residencial de internet5
 
8.8%
Celular pré-pago (dados limitados + aplicativos) Tenho um plano residencial de internet5
 
8.8%
Celular pré-pago (dados limitados + aplicativos)4
 
7.0%
Celular pré-pago (dados limitados + aplicativos) Por pontos de wi-fi abertos pela cidade (internet provida por governo/empresas)3
 
5.3%
Internet por redes de vizinhos3
 
5.3%
Internet celular pós-paga (franquia de dados + aplicativos)2
 
3.5%
Celular pré-pago (dados limitados + aplicativos) Por pontos de wi-fi abertos pela cidade (internet provida por governo/empresas) Tenho um plano residencial de internet2
 
3.5%
Só tenho acesso ao whatsapp no celular, porque é gratuito Celular pré-pago (dados limitados + aplicativos) Internet por redes de vizinhos2
 
3.5%
Centros públicos (espaços culturais, telecentros etc) Tenho um plano residencial de internet1
 
1.8%
Other values (24)24
42.1%

Length

2022-05-31T15:05:58.044765image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
internet83
 
9.1%
de74
 
8.1%
por53
 
5.8%
53
 
5.8%
celular44
 
4.8%
tenho35
 
3.8%
dados35
 
3.8%
aplicativos35
 
3.8%
plano26
 
2.9%
residencial26
 
2.9%
Other values (39)446
49.0%

Most occurring characters

ValueCountFrequency (%)
853
13.3%
e630
 
9.9%
a492
 
7.7%
o489
 
7.6%
r403
 
6.3%
i382
 
6.0%
n363
 
5.7%
t361
 
5.6%
s356
 
5.6%
d294
 
4.6%
Other values (31)1770
27.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5141
80.4%
Space Separator853
 
13.3%
Uppercase Letter127
 
2.0%
Close Punctuation64
 
1.0%
Open Punctuation64
 
1.0%
Other Punctuation56
 
0.9%
Dash Punctuation53
 
0.8%
Math Symbol35
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e630
12.3%
a492
9.6%
o489
9.5%
r403
 
7.8%
i382
 
7.4%
n363
 
7.1%
t361
 
7.0%
s356
 
6.9%
d294
 
5.7%
p289
 
5.6%
Other values (18)1082
21.0%
Uppercase Letter
ValueCountFrequency (%)
I37
29.1%
C35
27.6%
T26
20.5%
P18
14.2%
S9
 
7.1%
N2
 
1.6%
Other Punctuation
ValueCountFrequency (%)
/36
64.3%
,20
35.7%
Space Separator
ValueCountFrequency (%)
853
100.0%
Close Punctuation
ValueCountFrequency (%)
)64
100.0%
Open Punctuation
ValueCountFrequency (%)
(64
100.0%
Dash Punctuation
ValueCountFrequency (%)
-53
100.0%
Math Symbol
ValueCountFrequency (%)
+35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5268
82.4%
Common1125
 
17.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e630
12.0%
a492
9.3%
o489
9.3%
r403
 
7.6%
i382
 
7.3%
n363
 
6.9%
t361
 
6.9%
s356
 
6.8%
d294
 
5.6%
p289
 
5.5%
Other values (24)1209
22.9%
Common
ValueCountFrequency (%)
853
75.8%
)64
 
5.7%
(64
 
5.7%
-53
 
4.7%
/36
 
3.2%
+35
 
3.1%
,20
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII6314
98.8%
None79
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
853
13.5%
e630
 
10.0%
a492
 
7.8%
o489
 
7.7%
r403
 
6.4%
i382
 
6.1%
n363
 
5.7%
t361
 
5.7%
s356
 
5.6%
d294
 
4.7%
Other values (25)1691
26.8%
None
ValueCountFrequency (%)
é33
41.8%
ó20
25.3%
ú11
 
13.9%
ç11
 
13.9%
ã2
 
2.5%
à2
 
2.5%

perfap
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size584.0 B
Sim
55 
Não
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters171
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowSim
3rd rowSim
4th rowSim
5th rowSim

Common Values

ValueCountFrequency (%)
Sim55
96.5%
Não2
 
3.5%

Length

2022-05-31T15:05:58.186385image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:58.303074image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim55
96.5%
não2
 
3.5%

Most occurring characters

ValueCountFrequency (%)
S55
32.2%
i55
32.2%
m55
32.2%
N2
 
1.2%
ã2
 
1.2%
o2
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter114
66.7%
Uppercase Letter57
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i55
48.2%
m55
48.2%
ã2
 
1.8%
o2
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
S55
96.5%
N2
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
Latin171
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S55
32.2%
i55
32.2%
m55
32.2%
N2
 
1.2%
ã2
 
1.2%
o2
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII169
98.8%
None2
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S55
32.5%
i55
32.5%
m55
32.5%
N2
 
1.2%
o2
 
1.2%
None
ValueCountFrequency (%)
ã2
100.0%

topuso
Categorical

HIGH CORRELATION
MISSING

Distinct29
Distinct (%)52.7%
Missing2
Missing (%)3.5%
Memory size584.0 B
Instagram Facebook Whatsapp Twitter
Instagram Facebook Whatsapp
Instagram Facebook Whatsapp Tiktok Twitter Tinder, grindr outros apps de paquera Telegram
Instagram Whatsapp Twitter Tinder, grindr outros apps de paquera
Instagram Facebook Whatsapp Tinder, grindr outros apps de paquera
Other values (24)
28 

Length

Max length89
Median length74
Mean length49.32727273
Min length8

Characters and Unicode

Total characters2713
Distinct characters30
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)36.4%

Sample

1st rowInstagram Whatsapp Twitter Tinder, grindr outros apps de paquera
2nd rowInstagram Whatsapp Tiktok Twitter Tinder, grindr outros apps de paquera
3rd rowFacebook Whatsapp
4th rowInstagram Facebook Whatsapp Twitter
5th rowInstagram Facebook Whatsapp Tiktok Twitter Tinder, grindr outros apps de paquera Telegram

Common Values

ValueCountFrequency (%)
Instagram Facebook Whatsapp Twitter8
14.0%
Instagram Facebook Whatsapp8
14.0%
Instagram Facebook Whatsapp Tiktok Twitter Tinder, grindr outros apps de paquera Telegram5
 
8.8%
Instagram Whatsapp Twitter Tinder, grindr outros apps de paquera3
 
5.3%
Instagram Facebook Whatsapp Tinder, grindr outros apps de paquera3
 
5.3%
Instagram Facebook Whatsapp Twitter Tinder, grindr outros apps de paquera2
 
3.5%
Instagram Facebook Whatsapp Tiktok Twitter Tinder, grindr outros apps de paquera2
 
3.5%
Instagram Facebook Whatsapp Twitter Tinder, grindr outros apps de paquera Telegram2
 
3.5%
Instagram Facebook Whatsapp Tiktok Twitter2
 
3.5%
Instagram Facebook Tiktok1
 
1.8%
Other values (19)19
33.3%
(Missing)2
 
3.5%

Length

2022-05-31T15:05:58.467633image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
whatsapp51
14.6%
instagram50
14.3%
facebook46
13.2%
twitter32
9.2%
outros22
6.3%
paquera22
6.3%
de22
6.3%
apps22
6.3%
grindr22
6.3%
tinder22
6.3%
Other values (7)38
10.9%

Most occurring characters

ValueCountFrequency (%)
a333
12.3%
295
 
10.9%
r208
 
7.7%
t207
 
7.6%
e179
 
6.6%
p169
 
6.2%
o159
 
5.9%
s148
 
5.5%
n97
 
3.6%
i95
 
3.5%
Other values (20)823
30.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2158
79.5%
Space Separator295
 
10.9%
Uppercase Letter238
 
8.8%
Other Punctuation22
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a333
15.4%
r208
9.6%
t207
9.6%
e179
 
8.3%
p169
 
7.8%
o159
 
7.4%
s148
 
6.9%
n97
 
4.5%
i95
 
4.4%
g88
 
4.1%
Other values (10)475
22.0%
Uppercase Letter
ValueCountFrequency (%)
T87
36.6%
W51
21.4%
I50
21.0%
F46
19.3%
M1
 
0.4%
B1
 
0.4%
P1
 
0.4%
A1
 
0.4%
Space Separator
ValueCountFrequency (%)
295
100.0%
Other Punctuation
ValueCountFrequency (%)
,22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2396
88.3%
Common317
 
11.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a333
13.9%
r208
 
8.7%
t207
 
8.6%
e179
 
7.5%
p169
 
7.1%
o159
 
6.6%
s148
 
6.2%
n97
 
4.0%
i95
 
4.0%
g88
 
3.7%
Other values (18)713
29.8%
Common
ValueCountFrequency (%)
295
93.1%
,22
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII2713
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a333
12.3%
295
 
10.9%
r208
 
7.7%
t207
 
7.6%
e179
 
6.6%
p169
 
6.2%
o159
 
5.9%
s148
 
5.5%
n97
 
3.6%
i95
 
3.5%
Other values (20)823
30.3%

usopara
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct43
Distinct (%)79.6%
Missing3
Missing (%)5.3%
Memory size584.0 B
Trabalho Estudo Ativismo Lazer Grupos de apoio Se informar Conhecer gente nova Conectar com a família Fazer compras Acesso a serviços Flertes/relacionamento
Trabalho
 
3
Trabalho Lazer Se informar Conhecer gente nova Conectar com a família Acesso a serviços Flertes/relacionamento
 
2
Trabalho Estudo Lazer
 
2
Trabalho Lazer Conhecer gente nova
 
2
Other values (38)
40 

Length

Max length156
Median length90.5
Mean length74.01851852
Min length5

Characters and Unicode

Total characters3997
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)66.7%

Sample

1st rowTrabalho Estudo Ativismo Lazer Grupos de apoio Se informar Conhecer gente nova Flertes/relacionamento
2nd rowTrabalho Estudo Ativismo Lazer Se informar Conhecer gente nova Conectar com a família Fazer compras Acesso a serviços Flertes/relacionamento
3rd rowLazer Conectar com a família
4th rowTrabalho Estudo Lazer
5th rowEstudo Lazer Se informar Conhecer gente nova Fazer compras Flertes/relacionamento

Common Values

ValueCountFrequency (%)
Trabalho Estudo Ativismo Lazer Grupos de apoio Se informar Conhecer gente nova Conectar com a família Fazer compras Acesso a serviços Flertes/relacionamento5
 
8.8%
Trabalho3
 
5.3%
Trabalho Lazer Se informar Conhecer gente nova Conectar com a família Acesso a serviços Flertes/relacionamento2
 
3.5%
Trabalho Estudo Lazer2
 
3.5%
Trabalho Lazer Conhecer gente nova2
 
3.5%
Lazer2
 
3.5%
Trabalho Estudo Ativismo Lazer Grupos de apoio Se informar Conhecer gente nova Conectar com a família Flertes/relacionamento2
 
3.5%
Trabalho Lazer Grupos de apoio Se informar Conhecer gente nova Conectar com a família Fazer compras Acesso a serviços Flertes/relacionamento1
 
1.8%
Trabalho Se informar Conhecer gente nova Acesso a serviços Flertes/relacionamento1
 
1.8%
Trabalho Estudo Lazer Grupos de apoio Se informar Conhecer gente nova Conectar com a família Acesso a serviços Flertes/relacionamento1
 
1.8%
Other values (33)33
57.9%
(Missing)3
 
5.3%

Length

2022-05-31T15:05:58.695029image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
a47
 
8.4%
lazer45
 
8.0%
trabalho40
 
7.1%
conhecer33
 
5.9%
nova33
 
5.9%
gente33
 
5.9%
se31
 
5.5%
informar31
 
5.5%
estudo27
 
4.8%
conectar26
 
4.6%
Other values (11)215
38.3%

Most occurring characters

ValueCountFrequency (%)
507
12.7%
a413
 
10.3%
e411
 
10.3%
o389
 
9.7%
r326
 
8.2%
n208
 
5.2%
s186
 
4.7%
t156
 
3.9%
i155
 
3.9%
c148
 
3.7%
Other values (22)1098
27.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3166
79.2%
Space Separator507
 
12.7%
Uppercase Letter298
 
7.5%
Other Punctuation26
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a413
13.0%
e411
13.0%
o389
12.3%
r326
10.3%
n208
 
6.6%
s186
 
5.9%
t156
 
4.9%
i155
 
4.9%
c148
 
4.7%
m143
 
4.5%
Other values (12)631
19.9%
Uppercase Letter
ValueCountFrequency (%)
C59
19.8%
L45
15.1%
F42
14.1%
T40
13.4%
A39
13.1%
S31
10.4%
E27
9.1%
G15
 
5.0%
Space Separator
ValueCountFrequency (%)
507
100.0%
Other Punctuation
ValueCountFrequency (%)
/26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3464
86.7%
Common533
 
13.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a413
11.9%
e411
11.9%
o389
11.2%
r326
 
9.4%
n208
 
6.0%
s186
 
5.4%
t156
 
4.5%
i155
 
4.5%
c148
 
4.3%
m143
 
4.1%
Other values (20)929
26.8%
Common
ValueCountFrequency (%)
507
95.1%
/26
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII3950
98.8%
None47
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
507
12.8%
a413
 
10.5%
e411
 
10.4%
o389
 
9.8%
r326
 
8.3%
n208
 
5.3%
s186
 
4.7%
t156
 
3.9%
i155
 
3.9%
c148
 
3.7%
Other values (20)1051
26.6%
None
ValueCountFrequency (%)
í26
55.3%
ç21
44.7%

sitweb
Categorical

HIGH CORRELATION
MISSING

Distinct38
Distinct (%)71.7%
Missing4
Missing (%)7.0%
Memory size584.0 B
Nunca sofri nenhuma dessas situações
LGBTfobia
Racismo LGBTfobia Preconceito de classe social
 
2
LGBTfobia Preconceito de classe social
 
2
LGBTfobia Gordofobia Xingamentos e/ou humilhações
 
2
Other values (33)
33 

Length

Max length365
Median length243
Mean length94.26415094
Min length7

Characters and Unicode

Total characters4996
Distinct characters46
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)62.3%

Sample

1st rowRacismo A plataforma que utilizo não contempla minha identidade de gênero
2nd rowRacismo LGBTfobia Machismo Xingamentos e/ou humilhações
3rd rowRacismo Intolerância religiosa Xingamentos e/ou humilhações
4th rowLGBTfobia
5th rowMachismo Assédio sexual

Common Values

ValueCountFrequency (%)
Nunca sofri nenhuma dessas situações8
 
14.0%
LGBTfobia6
 
10.5%
Racismo LGBTfobia Preconceito de classe social2
 
3.5%
LGBTfobia Preconceito de classe social2
 
3.5%
LGBTfobia Gordofobia Xingamentos e/ou humilhações2
 
3.5%
Racismo A plataforma que utilizo não contempla minha identidade de gênero1
 
1.8%
Racismo LGBTfobia Preconceito de classe social Machismo Intolerância religiosa Xingamentos e/ou humilhações Ameaças psicológicas e/ou de violência física Assédio sexual A plataforma que utilizo não contempla minha identidade de gênero1
 
1.8%
LGBTfobia Preconceito de classe social Machismo Xingamentos e/ou humilhações Vazaram meus nudes Ameaças psicológicas e/ou de violência física Expuseram minha orientação sexual e identidade de gênero sem meu consentimento Assédio sexual Linchamento virtual1
 
1.8%
LGBTfobia Preconceito de classe social Machismo Intolerância religiosa Xingamentos e/ou humilhações Vazaram meus nudes Ameaças psicológicas e/ou de violência física Expuseram minha orientação sexual e identidade de gênero sem meu consentimento Assédio sexual1
 
1.8%
LGBTfobia Xingamentos e/ou humilhações Vazaram meus nudes Ameaças psicológicas e/ou de violência física Expuseram minha orientação sexual e identidade de gênero sem meu consentimento Assédio sexual Linchamento virtual1
 
1.8%
Other values (28)28
49.1%
(Missing)4
 
7.0%

Length

2022-05-31T15:05:58.870556image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
de50
 
8.0%
lgbtfobia38
 
6.1%
e/ou35
 
5.6%
sexual30
 
4.8%
classe22
 
3.5%
preconceito22
 
3.5%
social22
 
3.5%
xingamentos22
 
3.5%
humilhações22
 
3.5%
racismo20
 
3.2%
Other values (35)345
54.9%

Most occurring characters

ValueCountFrequency (%)
575
 
11.5%
e454
 
9.1%
a442
 
8.8%
i404
 
8.1%
s385
 
7.7%
o382
 
7.6%
n258
 
5.2%
c225
 
4.5%
m198
 
4.0%
l174
 
3.5%
Other values (36)1499
30.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4058
81.2%
Space Separator575
 
11.5%
Uppercase Letter328
 
6.6%
Other Punctuation35
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e454
11.2%
a442
10.9%
i404
10.0%
s385
 
9.5%
o382
 
9.4%
n258
 
6.4%
c225
 
5.5%
m198
 
4.9%
l174
 
4.3%
u167
 
4.1%
Other values (20)969
23.9%
Uppercase Letter
ValueCountFrequency (%)
L44
13.4%
G43
13.1%
T38
11.6%
B38
11.6%
A36
11.0%
X22
6.7%
P22
6.7%
R20
6.1%
M18
5.5%
I16
 
4.9%
Other values (4)31
9.5%
Space Separator
ValueCountFrequency (%)
575
100.0%
Other Punctuation
ValueCountFrequency (%)
/35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4386
87.8%
Common610
 
12.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e454
 
10.4%
a442
 
10.1%
i404
 
9.2%
s385
 
8.8%
o382
 
8.7%
n258
 
5.9%
c225
 
5.1%
m198
 
4.5%
l174
 
4.0%
u167
 
3.8%
Other values (34)1297
29.6%
Common
ValueCountFrequency (%)
575
94.3%
/35
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII4808
96.2%
None188
 
3.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
575
12.0%
e454
 
9.4%
a442
 
9.2%
i404
 
8.4%
s385
 
8.0%
o382
 
7.9%
n258
 
5.4%
c225
 
4.7%
m198
 
4.1%
l174
 
3.6%
Other values (28)1311
27.3%
None
ValueCountFrequency (%)
ç54
28.7%
õ30
16.0%
ê28
14.9%
é19
 
10.1%
â16
 
8.5%
ã15
 
8.0%
ó13
 
6.9%
í13
 
6.9%

continvs
Categorical

HIGH CORRELATION
MISSING

Distinct19
Distinct (%)36.5%
Missing5
Missing (%)8.8%
Memory size584.0 B
Nunca tive esse tipo de problemas
19 
Conta bloqueada/excluída
Post removido Conta bloqueada/excluída
Post removido
Conta bloqueada/excluída Conta invadida (ex. alguém entrou no meu perfil fingindo que era eu) Conta roubada (ex. nao consegui mais ter acesso)
Other values (14)
15 

Length

Max length449
Median length289
Mean length84.03846154
Min length13

Characters and Unicode

Total characters4370
Distinct characters38
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)25.0%

Sample

1st rowPost removido Palavras censuradas (ex. nao consigo postar a palavra “sapatao” no insta)
2nd rowNunca tive esse tipo de problemas
3rd rowNunca tive esse tipo de problemas
4th rowPost removido Conta bloqueada/excluída
5th rowConta bloqueada/excluída

Common Values

ValueCountFrequency (%)
Nunca tive esse tipo de problemas19
33.3%
Conta bloqueada/excluída6
 
10.5%
Post removido Conta bloqueada/excluída5
 
8.8%
Post removido4
 
7.0%
Conta bloqueada/excluída Conta invadida (ex. alguém entrou no meu perfil fingindo que era eu) Conta roubada (ex. nao consegui mais ter acesso)3
 
5.3%
Post removido Conta bloqueada/excluída Palavras censuradas (ex. nao consigo postar a palavra “sapatao” no insta)2
 
3.5%
Post removido Palavras censuradas (ex. nao consigo postar a palavra “sapatao” no insta)1
 
1.8%
Post removido Conta bloqueada/excluída Palavras censuradas (ex. nao consigo postar a palavra “sapatao” no insta) Conta invadida (ex. alguém entrou no meu perfil fingindo que era eu)1
 
1.8%
Palavras censuradas (ex. nao consigo postar a palavra “sapatao” no insta)1
 
1.8%
Conta bloqueada/excluída Palavras censuradas (ex. nao consigo postar a palavra “sapatao” no insta) Dados de telefone vazados1
 
1.8%
Other values (9)9
15.8%
(Missing)5
 
8.8%

Length

2022-05-31T15:05:59.012178image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
conta44
 
6.6%
ex39
 
5.8%
de27
 
4.0%
tive26
 
3.9%
nao25
 
3.7%
problemas24
 
3.6%
bloqueada/excluída24
 
3.6%
no24
 
3.6%
meu24
 
3.6%
post20
 
3.0%
Other values (47)393
58.7%

Most occurring characters

ValueCountFrequency (%)
618
14.1%
a486
 
11.1%
e409
 
9.4%
o368
 
8.4%
s227
 
5.2%
n224
 
5.1%
i201
 
4.6%
d192
 
4.4%
u182
 
4.2%
t176
 
4.0%
Other values (28)1287
29.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3482
79.7%
Space Separator618
 
14.1%
Uppercase Letter105
 
2.4%
Other Punctuation63
 
1.4%
Open Punctuation39
 
0.9%
Close Punctuation39
 
0.9%
Initial Punctuation12
 
0.3%
Final Punctuation12
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a486
14.0%
e409
11.7%
o368
10.6%
s227
 
6.5%
n224
 
6.4%
i201
 
5.8%
d192
 
5.5%
u182
 
5.2%
t176
 
5.1%
r162
 
4.7%
Other values (16)855
24.6%
Uppercase Letter
ValueCountFrequency (%)
C44
41.9%
P32
30.5%
N19
18.1%
T7
 
6.7%
D3
 
2.9%
Other Punctuation
ValueCountFrequency (%)
.39
61.9%
/24
38.1%
Space Separator
ValueCountFrequency (%)
618
100.0%
Open Punctuation
ValueCountFrequency (%)
(39
100.0%
Close Punctuation
ValueCountFrequency (%)
)39
100.0%
Initial Punctuation
ValueCountFrequency (%)
12
100.0%
Final Punctuation
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3587
82.1%
Common783
 
17.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a486
13.5%
e409
11.4%
o368
 
10.3%
s227
 
6.3%
n224
 
6.2%
i201
 
5.6%
d192
 
5.4%
u182
 
5.1%
t176
 
4.9%
r162
 
4.5%
Other values (21)960
26.8%
Common
ValueCountFrequency (%)
618
78.9%
(39
 
5.0%
.39
 
5.0%
)39
 
5.0%
/24
 
3.1%
12
 
1.5%
12
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII4296
98.3%
None50
 
1.1%
Punctuation24
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
618
14.4%
a486
11.3%
e409
 
9.5%
o368
 
8.6%
s227
 
5.3%
n224
 
5.2%
i201
 
4.7%
d192
 
4.5%
u182
 
4.2%
t176
 
4.1%
Other values (21)1213
28.2%
None
ValueCountFrequency (%)
í24
48.0%
é12
24.0%
ç7
 
14.0%
ã5
 
10.0%
õ2
 
4.0%
Punctuation
ValueCountFrequency (%)
12
50.0%
12
50.0%

netservpub
Categorical

HIGH CORRELATION

Distinct4
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size584.0 B
Sim, durante a pandemia
21 
Sim, antes e durante a pandemia
17 
Nunca precisei
10 
Não tenho certeza

Length

Max length31
Median length23
Mean length22.85964912
Min length14

Characters and Unicode

Total characters1303
Distinct characters20
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim, antes e durante a pandemia
2nd rowNunca precisei
3rd rowNão tenho certeza
4th rowSim, durante a pandemia
5th rowSim, durante a pandemia

Common Values

ValueCountFrequency (%)
Sim, durante a pandemia21
36.8%
Sim, antes e durante a pandemia17
29.8%
Nunca precisei10
17.5%
Não tenho certeza9
15.8%

Length

2022-05-31T15:05:59.134889image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:59.271485image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim38
16.3%
durante38
16.3%
a38
16.3%
pandemia38
16.3%
antes17
7.3%
e17
7.3%
nunca10
 
4.3%
precisei10
 
4.3%
não9
 
3.9%
tenho9
 
3.9%

Most occurring characters

ValueCountFrequency (%)
a188
14.4%
176
13.5%
e157
12.0%
n112
8.6%
i96
 
7.4%
m76
 
5.8%
d76
 
5.8%
t73
 
5.6%
r57
 
4.4%
p48
 
3.7%
Other values (10)244
18.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1032
79.2%
Space Separator176
 
13.5%
Uppercase Letter57
 
4.4%
Other Punctuation38
 
2.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a188
18.2%
e157
15.2%
n112
10.9%
i96
9.3%
m76
7.4%
d76
7.4%
t73
 
7.1%
r57
 
5.5%
p48
 
4.7%
u48
 
4.7%
Other values (6)101
9.8%
Uppercase Letter
ValueCountFrequency (%)
S38
66.7%
N19
33.3%
Space Separator
ValueCountFrequency (%)
176
100.0%
Other Punctuation
ValueCountFrequency (%)
,38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1089
83.6%
Common214
 
16.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a188
17.3%
e157
14.4%
n112
10.3%
i96
8.8%
m76
7.0%
d76
7.0%
t73
 
6.7%
r57
 
5.2%
p48
 
4.4%
u48
 
4.4%
Other values (8)158
14.5%
Common
ValueCountFrequency (%)
176
82.2%
,38
 
17.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII1294
99.3%
None9
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a188
14.5%
176
13.6%
e157
12.1%
n112
8.7%
i96
7.4%
m76
 
5.9%
d76
 
5.9%
t73
 
5.6%
r57
 
4.4%
p48
 
3.7%
Other values (9)235
18.2%
None
ValueCountFrequency (%)
ã9
100.0%

tpnetserv
Categorical

HIGH CORRELATION
MISSING

Distinct21
Distinct (%)63.6%
Missing24
Missing (%)42.1%
Memory size584.0 B
Auxílio emergencial / cadastro único
Estudos durante a pandemia
Carteira de trabalho digital Auxílio emergencial / cadastro único
Carteira de trabalho digital Auxílio emergencial / cadastro único Bolsa família
Carteira de trabalho digital
Other values (16)
16 

Length

Max length308
Median length146
Mean length95.87878788
Min length26

Characters and Unicode

Total characters3164
Distinct characters37
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)48.5%

Sample

1st rowDocumentos (título de eleitor, cpf, rg) Certificados diversos (antecedentes criminais, cadastro positivo etc)
2nd rowAuxílio emergencial / cadastro único
3rd rowEstudos durante a pandemia
4th rowAuxílio emergencial / cadastro único
5th rowAuxílio emergencial / cadastro único

Common Values

ValueCountFrequency (%)
Auxílio emergencial / cadastro único9
 
15.8%
Estudos durante a pandemia2
 
3.5%
Carteira de trabalho digital Auxílio emergencial / cadastro único2
 
3.5%
Carteira de trabalho digital Auxílio emergencial / cadastro único Bolsa família2
 
3.5%
Carteira de trabalho digital2
 
3.5%
Documentos (título de eleitor, cpf, rg) Certificados diversos (antecedentes criminais, cadastro positivo etc)1
 
1.8%
Carteira de trabalho digital Auxílio emergencial / cadastro único Documentos (título de eleitor, cpf, rg)1
 
1.8%
Carteira de trabalho digital Auxílio emergencial / cadastro único Bolsa família Estudos durante a pandemia Documentos (título de eleitor, cpf, rg) Certificados diversos (antecedentes criminais, cadastro positivo etc) Acesso a serviços essenciais (luz, água, saneamento etc)1
 
1.8%
Auxílio emergencial / cadastro único Documentos (título de eleitor, cpf, rg) Certificados diversos (antecedentes criminais, cadastro positivo etc)1
 
1.8%
Auxílio emergencial / cadastro único Bolsa família Estudos durante a pandemia Documentos (título de eleitor, cpf, rg) Certificados diversos (antecedentes criminais, cadastro positivo etc) Acesso a serviços essenciais (luz, água, saneamento etc)1
 
1.8%
Other values (11)11
19.3%
(Missing)24
42.1%

Length

2022-05-31T15:05:59.421086image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
cadastro33
 
7.7%
de29
 
6.8%
auxílio25
 
5.9%
25
 
5.9%
único25
 
5.9%
emergencial25
 
5.9%
a17
 
4.0%
etc13
 
3.1%
documentos12
 
2.8%
rg12
 
2.8%
Other values (27)210
49.3%

Most occurring characters

ValueCountFrequency (%)
393
12.4%
a295
 
9.3%
e279
 
8.8%
i229
 
7.2%
o218
 
6.9%
t194
 
6.1%
r180
 
5.7%
s176
 
5.6%
c157
 
5.0%
d141
 
4.5%
Other values (27)902
28.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2567
81.1%
Space Separator393
 
12.4%
Uppercase Letter87
 
2.7%
Other Punctuation67
 
2.1%
Close Punctuation25
 
0.8%
Open Punctuation25
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a295
11.5%
e279
10.9%
i229
 
8.9%
o218
 
8.5%
t194
 
7.6%
r180
 
7.0%
s176
 
6.9%
c157
 
6.1%
d141
 
5.5%
n125
 
4.9%
Other values (16)573
22.3%
Uppercase Letter
ValueCountFrequency (%)
A30
34.5%
C20
23.0%
D12
 
13.8%
E12
 
13.8%
B8
 
9.2%
P5
 
5.7%
Other Punctuation
ValueCountFrequency (%)
,42
62.7%
/25
37.3%
Space Separator
ValueCountFrequency (%)
393
100.0%
Close Punctuation
ValueCountFrequency (%)
)25
100.0%
Open Punctuation
ValueCountFrequency (%)
(25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2654
83.9%
Common510
 
16.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a295
11.1%
e279
10.5%
i229
 
8.6%
o218
 
8.2%
t194
 
7.3%
r180
 
6.8%
s176
 
6.6%
c157
 
5.9%
d141
 
5.3%
n125
 
4.7%
Other values (22)660
24.9%
Common
ValueCountFrequency (%)
393
77.1%
,42
 
8.2%
)25
 
4.9%
(25
 
4.9%
/25
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII3081
97.4%
None83
 
2.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
393
12.8%
a295
 
9.6%
e279
 
9.1%
i229
 
7.4%
o218
 
7.1%
t194
 
6.3%
r180
 
5.8%
s176
 
5.7%
c157
 
5.1%
d141
 
4.6%
Other values (22)819
26.6%
None
ValueCountFrequency (%)
í45
54.2%
ú25
30.1%
ç5
 
6.0%
á5
 
6.0%
é3
 
3.6%

difserv
Categorical

HIGH CORRELATION
MISSING

Distinct17
Distinct (%)51.5%
Missing24
Missing (%)42.1%
Memory size584.0 B
Não tive dificuldade
Dificuldade em acessar a internet
Dificuldade em encontrar informações corretas nos sites e em buscas
Site/app indisponível
 
1
Dificuldade em acessar a internet Dificuldade em encontrar informações corretas nos sites e em buscas Site/app indisponível Site/app muito complicado de usar Plano de dados não permite acessar esses serviços
 
1
Other values (12)
12 

Length

Max length355
Median length218
Mean length70.3030303
Min length20

Characters and Unicode

Total characters2320
Distinct characters30
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)42.4%

Sample

1st rowDificuldade em encontrar informações corretas nos sites e em buscas
2nd rowDificuldade em acessar a internet
3rd rowDificuldade em encontrar informações corretas nos sites e em buscas
4th rowDificuldade em acessar a internet
5th rowDificuldade em acessar a internet

Common Values

ValueCountFrequency (%)
Não tive dificuldade9
 
15.8%
Dificuldade em acessar a internet8
 
14.0%
Dificuldade em encontrar informações corretas nos sites e em buscas2
 
3.5%
Site/app indisponível1
 
1.8%
Dificuldade em acessar a internet Dificuldade em encontrar informações corretas nos sites e em buscas Site/app indisponível Site/app muito complicado de usar Plano de dados não permite acessar esses serviços1
 
1.8%
Dificuldade em encontrar informações corretas nos sites e em buscas Site/app indisponível Plano de dados não permite acessar esses serviços Não tive acesso a um computador ou celular para usar1
 
1.8%
Site/app pediram dados que eu não tinha no momento Site/app muito complicado de usar Plano de dados não permite acessar esses serviços1
 
1.8%
Dificuldade em acessar a internet Site/app indisponível1
 
1.8%
Dificuldade em acessar a internet Dificuldade em encontrar informações corretas nos sites e em buscas Site/app indisponível Site/app pediram dados que eu não tinha no momento Site/app muito complicado de usar Plano de dados não permite acessar esses serviços Tive que emprestar um computador ou celular Não tive acesso a um computador ou celular para usar1
 
1.8%
Site/app indisponível Site/app muito complicado de usar1
 
1.8%
Other values (7)7
 
12.3%
(Missing)24
42.1%

Length

2022-05-31T15:05:59.573367image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
dificuldade31
 
8.7%
em30
 
8.5%
não22
 
6.2%
acessar19
 
5.4%
a18
 
5.1%
site/app17
 
4.8%
tive16
 
4.5%
internet14
 
3.9%
de10
 
2.8%
dados9
 
2.5%
Other values (28)169
47.6%

Most occurring characters

ValueCountFrequency (%)
322
13.9%
e260
11.2%
a201
 
8.7%
i169
 
7.3%
s156
 
6.7%
o133
 
5.7%
d123
 
5.3%
r120
 
5.2%
t110
 
4.7%
c102
 
4.4%
Other values (20)624
26.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1921
82.8%
Space Separator322
 
13.9%
Uppercase Letter60
 
2.6%
Other Punctuation17
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e260
13.5%
a201
10.5%
i169
 
8.8%
s156
 
8.1%
o133
 
6.9%
d123
 
6.4%
r120
 
6.2%
t110
 
5.7%
c102
 
5.3%
n102
 
5.3%
Other values (13)445
23.2%
Uppercase Letter
ValueCountFrequency (%)
D22
36.7%
S17
28.3%
N13
21.7%
P5
 
8.3%
T3
 
5.0%
Space Separator
ValueCountFrequency (%)
322
100.0%
Other Punctuation
ValueCountFrequency (%)
/17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1981
85.4%
Common339
 
14.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e260
13.1%
a201
 
10.1%
i169
 
8.5%
s156
 
7.9%
o133
 
6.7%
d123
 
6.2%
r120
 
6.1%
t110
 
5.6%
c102
 
5.1%
n102
 
5.1%
Other values (18)505
25.5%
Common
ValueCountFrequency (%)
322
95.0%
/17
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2269
97.8%
None51
 
2.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
322
14.2%
e260
11.5%
a201
 
8.9%
i169
 
7.4%
s156
 
6.9%
o133
 
5.9%
d123
 
5.4%
r120
 
5.3%
t110
 
4.8%
c102
 
4.5%
Other values (16)573
25.3%
None
ValueCountFrequency (%)
ã22
43.1%
ç13
25.5%
õ8
 
15.7%
í8
 
15.7%

cadbio
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size584.0 B
Sim
41 
Não
16 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters171
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão
2nd rowNão
3rd rowNão
4th rowNão
5th rowSim

Common Values

ValueCountFrequency (%)
Sim41
71.9%
Não16
 
28.1%

Length

2022-05-31T15:05:59.735931image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:05:59.868579image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim41
71.9%
não16
 
28.1%

Most occurring characters

ValueCountFrequency (%)
S41
24.0%
i41
24.0%
m41
24.0%
N16
 
9.4%
ã16
 
9.4%
o16
 
9.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter114
66.7%
Uppercase Letter57
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i41
36.0%
m41
36.0%
ã16
 
14.0%
o16
 
14.0%
Uppercase Letter
ValueCountFrequency (%)
S41
71.9%
N16
 
28.1%

Most occurring scripts

ValueCountFrequency (%)
Latin171
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S41
24.0%
i41
24.0%
m41
24.0%
N16
 
9.4%
ã16
 
9.4%
o16
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII155
90.6%
None16
 
9.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S41
26.5%
i41
26.5%
m41
26.5%
N16
 
10.3%
o16
 
10.3%
None
ValueCountFrequency (%)
ã16
100.0%

confbio
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)5.4%
Missing1
Missing (%)1.8%
Memory size584.0 B
Não
20 
Depende da situação
20 
Sim
16 

Length

Max length19
Median length3
Mean length8.714285714
Min length3

Characters and Unicode

Total characters488
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão
2nd rowNão
3rd rowDepende da situação
4th rowDepende da situação
5th rowSim

Common Values

ValueCountFrequency (%)
Não20
35.1%
Depende da situação20
35.1%
Sim16
28.1%
(Missing)1
 
1.8%

Length

2022-05-31T15:06:00.021167image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:06:00.155805image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não20
20.8%
depende20
20.8%
da20
20.8%
situação20
20.8%
sim16
16.7%

Most occurring characters

ValueCountFrequency (%)
e60
12.3%
40
 
8.2%
o40
 
8.2%
d40
 
8.2%
ã40
 
8.2%
a40
 
8.2%
i36
 
7.4%
ç20
 
4.1%
u20
 
4.1%
t20
 
4.1%
Other values (7)132
27.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter392
80.3%
Uppercase Letter56
 
11.5%
Space Separator40
 
8.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e60
15.3%
o40
10.2%
d40
10.2%
ã40
10.2%
a40
10.2%
i36
9.2%
ç20
 
5.1%
u20
 
5.1%
t20
 
5.1%
s20
 
5.1%
Other values (3)56
14.3%
Uppercase Letter
ValueCountFrequency (%)
N20
35.7%
D20
35.7%
S16
28.6%
Space Separator
ValueCountFrequency (%)
40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin448
91.8%
Common40
 
8.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e60
13.4%
o40
 
8.9%
d40
 
8.9%
ã40
 
8.9%
a40
 
8.9%
i36
 
8.0%
ç20
 
4.5%
u20
 
4.5%
t20
 
4.5%
N20
 
4.5%
Other values (6)112
25.0%
Common
ValueCountFrequency (%)
40
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII428
87.7%
None60
 
12.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e60
14.0%
40
9.3%
o40
9.3%
d40
9.3%
a40
9.3%
i36
 
8.4%
u20
 
4.7%
t20
 
4.7%
N20
 
4.7%
s20
 
4.7%
Other values (5)92
21.5%
None
ValueCountFrequency (%)
ã40
66.7%
ç20
33.3%

cinema
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size584.0 B
Quase nunca vou
40 
Vou com frequência
10 
Nunca fui

Length

Max length18
Median length15
Mean length14.78947368
Min length9

Characters and Unicode

Total characters843
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowQuase nunca vou
2nd rowQuase nunca vou
3rd rowNunca fui
4th rowQuase nunca vou
5th rowQuase nunca vou

Common Values

ValueCountFrequency (%)
Quase nunca vou40
70.2%
Vou com frequência10
 
17.5%
Nunca fui7
 
12.3%

Length

2022-05-31T15:06:00.273492image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:06:00.422092image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
vou50
30.5%
nunca47
28.7%
quase40
24.4%
com10
 
6.1%
frequência10
 
6.1%
fui7
 
4.3%

Most occurring characters

ValueCountFrequency (%)
u154
18.3%
107
12.7%
a97
11.5%
n97
11.5%
c67
7.9%
o60
 
7.1%
e50
 
5.9%
v40
 
4.7%
Q40
 
4.7%
s40
 
4.7%
Other values (8)91
10.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter679
80.5%
Space Separator107
 
12.7%
Uppercase Letter57
 
6.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u154
22.7%
a97
14.3%
n97
14.3%
c67
9.9%
o60
 
8.8%
e50
 
7.4%
v40
 
5.9%
s40
 
5.9%
f17
 
2.5%
i17
 
2.5%
Other values (4)40
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
Q40
70.2%
V10
 
17.5%
N7
 
12.3%
Space Separator
ValueCountFrequency (%)
107
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin736
87.3%
Common107
 
12.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
u154
20.9%
a97
13.2%
n97
13.2%
c67
9.1%
o60
 
8.2%
e50
 
6.8%
v40
 
5.4%
Q40
 
5.4%
s40
 
5.4%
f17
 
2.3%
Other values (7)74
10.1%
Common
ValueCountFrequency (%)
107
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII833
98.8%
None10
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
u154
18.5%
107
12.8%
a97
11.6%
n97
11.6%
c67
8.0%
o60
 
7.2%
e50
 
6.0%
v40
 
4.8%
Q40
 
4.8%
s40
 
4.8%
Other values (7)81
9.7%
None
ValueCountFrequency (%)
ê10
100.0%

museus
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size584.0 B
Quase nunca vou
34 
Vou com frequência
12 
Nunca fui
11 

Length

Max length18
Median length15
Mean length14.47368421
Min length9

Characters and Unicode

Total characters825
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowVou com frequência
2nd rowQuase nunca vou
3rd rowQuase nunca vou
4th rowNunca fui
5th rowQuase nunca vou

Common Values

ValueCountFrequency (%)
Quase nunca vou34
59.6%
Vou com frequência12
 
21.1%
Nunca fui11
 
19.3%

Length

2022-05-31T15:06:00.541774image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:06:00.650525image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
vou46
28.7%
nunca45
28.1%
quase34
21.2%
com12
 
7.5%
frequência12
 
7.5%
fui11
 
6.9%

Most occurring characters

ValueCountFrequency (%)
u148
17.9%
103
12.5%
a91
11.0%
n91
11.0%
c69
8.4%
o58
 
7.0%
e46
 
5.6%
v34
 
4.1%
Q34
 
4.1%
s34
 
4.1%
Other values (8)117
14.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter665
80.6%
Space Separator103
 
12.5%
Uppercase Letter57
 
6.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u148
22.3%
a91
13.7%
n91
13.7%
c69
10.4%
o58
 
8.7%
e46
 
6.9%
v34
 
5.1%
s34
 
5.1%
f23
 
3.5%
i23
 
3.5%
Other values (4)48
 
7.2%
Uppercase Letter
ValueCountFrequency (%)
Q34
59.6%
V12
 
21.1%
N11
 
19.3%
Space Separator
ValueCountFrequency (%)
103
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin722
87.5%
Common103
 
12.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
u148
20.5%
a91
12.6%
n91
12.6%
c69
9.6%
o58
 
8.0%
e46
 
6.4%
v34
 
4.7%
Q34
 
4.7%
s34
 
4.7%
f23
 
3.2%
Other values (7)94
13.0%
Common
ValueCountFrequency (%)
103
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII813
98.5%
None12
 
1.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
u148
18.2%
103
12.7%
a91
11.2%
n91
11.2%
c69
8.5%
o58
 
7.1%
e46
 
5.7%
v34
 
4.2%
Q34
 
4.2%
s34
 
4.2%
Other values (7)105
12.9%
None
ValueCountFrequency (%)
ê12
100.0%

biblio
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size584.0 B
Sim, mas não frequento
28 
Não
25 
Sim, e frequento

Length

Max length22
Median length16
Mean length13.24561404
Min length3

Characters and Unicode

Total characters755
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão
2nd rowSim, e frequento
3rd rowSim, mas não frequento
4th rowSim, mas não frequento
5th rowSim, mas não frequento

Common Values

ValueCountFrequency (%)
Sim, mas não frequento28
49.1%
Não25
43.9%
Sim, e frequento4
 
7.0%

Length

2022-05-31T15:06:00.766173image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:06:00.894829image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não53
35.6%
sim32
21.5%
frequento32
21.5%
mas28
18.8%
e4
 
2.7%

Most occurring characters

ValueCountFrequency (%)
92
12.2%
o85
11.3%
e68
 
9.0%
m60
 
7.9%
n60
 
7.9%
ã53
 
7.0%
r32
 
4.2%
t32
 
4.2%
u32
 
4.2%
q32
 
4.2%
Other values (7)209
27.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter574
76.0%
Space Separator92
 
12.2%
Uppercase Letter57
 
7.5%
Other Punctuation32
 
4.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o85
14.8%
e68
11.8%
m60
10.5%
n60
10.5%
ã53
9.2%
r32
 
5.6%
t32
 
5.6%
u32
 
5.6%
q32
 
5.6%
f32
 
5.6%
Other values (3)88
15.3%
Uppercase Letter
ValueCountFrequency (%)
S32
56.1%
N25
43.9%
Space Separator
ValueCountFrequency (%)
92
100.0%
Other Punctuation
ValueCountFrequency (%)
,32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin631
83.6%
Common124
 
16.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
o85
13.5%
e68
10.8%
m60
9.5%
n60
9.5%
ã53
 
8.4%
r32
 
5.1%
t32
 
5.1%
u32
 
5.1%
q32
 
5.1%
S32
 
5.1%
Other values (5)145
23.0%
Common
ValueCountFrequency (%)
92
74.2%
,32
 
25.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII702
93.0%
None53
 
7.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
92
13.1%
o85
12.1%
e68
 
9.7%
m60
 
8.5%
n60
 
8.5%
r32
 
4.6%
t32
 
4.6%
u32
 
4.6%
q32
 
4.6%
S32
 
4.6%
Other values (6)177
25.2%
None
ValueCountFrequency (%)
ã53
100.0%

ler
Categorical

HIGH CORRELATION

Distinct4
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size584.0 B
Sim, leio com frequência a livros, revistas digitais e/ou artigos online
22 
Sim, mas leio com pouca frequência
20 
Não, não tenho esse costume
11 
Quase nunca paro para ler

Length

Max length72
Median length34
Mean length46.68421053
Min length25

Characters and Unicode

Total characters2661
Distinct characters27
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim, leio com frequência a livros, revistas digitais e/ou artigos online
2nd rowSim, leio com frequência a livros, revistas digitais e/ou artigos online
3rd rowSim, mas leio com pouca frequência
4th rowNão, não tenho esse costume
5th rowSim, mas leio com pouca frequência

Common Values

ValueCountFrequency (%)
Sim, leio com frequência a livros, revistas digitais e/ou artigos online22
38.6%
Sim, mas leio com pouca frequência20
35.1%
Não, não tenho esse costume11
19.3%
Quase nunca paro para ler4
 
7.0%

Length

2022-05-31T15:06:01.027475image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:06:01.169095image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
sim42
 
9.6%
com42
 
9.6%
frequência42
 
9.6%
leio42
 
9.6%
não22
 
5.0%
a22
 
5.0%
livros22
 
5.0%
revistas22
 
5.0%
digitais22
 
5.0%
e/ou22
 
5.0%
Other values (12)137
31.4%

Most occurring characters

ValueCountFrequency (%)
380
14.3%
i280
 
10.5%
o240
 
9.0%
e202
 
7.6%
a190
 
7.1%
s167
 
6.3%
r120
 
4.5%
c119
 
4.5%
n116
 
4.4%
m115
 
4.3%
Other values (17)732
27.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2127
79.9%
Space Separator380
 
14.3%
Other Punctuation97
 
3.6%
Uppercase Letter57
 
2.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i280
13.2%
o240
11.3%
e202
9.5%
a190
 
8.9%
s167
 
7.9%
r120
 
5.6%
c119
 
5.6%
n116
 
5.5%
m115
 
5.4%
u103
 
4.8%
Other values (11)475
22.3%
Uppercase Letter
ValueCountFrequency (%)
S42
73.7%
N11
 
19.3%
Q4
 
7.0%
Other Punctuation
ValueCountFrequency (%)
,75
77.3%
/22
 
22.7%
Space Separator
ValueCountFrequency (%)
380
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2184
82.1%
Common477
 
17.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
i280
12.8%
o240
11.0%
e202
 
9.2%
a190
 
8.7%
s167
 
7.6%
r120
 
5.5%
c119
 
5.4%
n116
 
5.3%
m115
 
5.3%
u103
 
4.7%
Other values (14)532
24.4%
Common
ValueCountFrequency (%)
380
79.7%
,75
 
15.7%
/22
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII2597
97.6%
None64
 
2.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
380
14.6%
i280
10.8%
o240
 
9.2%
e202
 
7.8%
a190
 
7.3%
s167
 
6.4%
r120
 
4.6%
c119
 
4.6%
n116
 
4.5%
m115
 
4.4%
Other values (15)668
25.7%
None
ValueCountFrequency (%)
ê42
65.6%
ã22
34.4%

bailes
Categorical

HIGH CORRELATION

Distinct5
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size584.0 B
Extremamente importante
15 
Nada importante
13 
Importante
13 
Pouco importante
12 
Muito importante

Length

Max length23
Median length16
Mean length16.24561404
Min length10

Characters and Unicode

Total characters926
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowExtremamente importante
2nd rowExtremamente importante
3rd rowNada importante
4th rowNada importante
5th rowImportante

Common Values

ValueCountFrequency (%)
Extremamente importante15
26.3%
Nada importante13
22.8%
Importante13
22.8%
Pouco importante12
21.1%
Muito importante4
 
7.0%

Length

2022-05-31T15:06:01.318695image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:06:01.451339image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
importante57
56.4%
extremamente15
 
14.9%
nada13
 
12.9%
pouco12
 
11.9%
muito4
 
4.0%

Most occurring characters

ValueCountFrequency (%)
t148
16.0%
e102
11.0%
a98
10.6%
m87
9.4%
o85
9.2%
r72
7.8%
n72
7.8%
p57
 
6.2%
i48
 
5.2%
44
 
4.8%
Other values (9)113
12.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter825
89.1%
Uppercase Letter57
 
6.2%
Space Separator44
 
4.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t148
17.9%
e102
12.4%
a98
11.9%
m87
10.5%
o85
10.3%
r72
8.7%
n72
8.7%
p57
 
6.9%
i48
 
5.8%
u16
 
1.9%
Other values (3)40
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
E15
26.3%
N13
22.8%
I13
22.8%
P12
21.1%
M4
 
7.0%
Space Separator
ValueCountFrequency (%)
44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin882
95.2%
Common44
 
4.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
t148
16.8%
e102
11.6%
a98
11.1%
m87
9.9%
o85
9.6%
r72
8.2%
n72
8.2%
p57
 
6.5%
i48
 
5.4%
u16
 
1.8%
Other values (8)97
11.0%
Common
ValueCountFrequency (%)
44
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII926
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t148
16.0%
e102
11.0%
a98
10.6%
m87
9.4%
o85
9.2%
r72
7.8%
n72
7.8%
p57
 
6.2%
i48
 
5.2%
44
 
4.8%
Other values (9)113
12.2%

eventos
Categorical

HIGH CORRELATION

Distinct4
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size584.0 B
Sim, participo com frequência de eventos dentro e fora da favela onde vivo
28 
Não, os ingressos para esses eventos são caros
14 
Não, é caro me locomover até eles
10 
Sim, participo com frequência apenas de eventos dentro da favela onde vivo

Length

Max length74
Median length74
Mean length59.92982456
Min length33

Characters and Unicode

Total characters3416
Distinct characters25
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim, participo com frequência de eventos dentro e fora da favela onde vivo
2nd rowSim, participo com frequência apenas de eventos dentro da favela onde vivo
3rd rowNão, os ingressos para esses eventos são caros
4th rowNão, é caro me locomover até eles
5th rowNão, os ingressos para esses eventos são caros

Common Values

ValueCountFrequency (%)
Sim, participo com frequência de eventos dentro e fora da favela onde vivo28
49.1%
Não, os ingressos para esses eventos são caros14
24.6%
Não, é caro me locomover até eles10
 
17.5%
Sim, participo com frequência apenas de eventos dentro da favela onde vivo5
 
8.8%

Length

2022-05-31T15:06:01.573053image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:06:01.695729image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
eventos47
 
7.8%
sim33
 
5.4%
participo33
 
5.4%
com33
 
5.4%
frequência33
 
5.4%
de33
 
5.4%
dentro33
 
5.4%
da33
 
5.4%
favela33
 
5.4%
onde33
 
5.4%
Other values (17)262
43.2%

Most occurring characters

ValueCountFrequency (%)
549
16.1%
e374
10.9%
o360
10.5%
a265
 
7.8%
r189
 
5.5%
s188
 
5.5%
i179
 
5.2%
n165
 
4.8%
v156
 
4.6%
c133
 
3.9%
Other values (15)858
25.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2753
80.6%
Space Separator549
 
16.1%
Other Punctuation57
 
1.7%
Uppercase Letter57
 
1.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e374
13.6%
o360
13.1%
a265
9.6%
r189
 
6.9%
s188
 
6.8%
i179
 
6.5%
n165
 
6.0%
v156
 
5.7%
c133
 
4.8%
d132
 
4.8%
Other values (11)612
22.2%
Uppercase Letter
ValueCountFrequency (%)
S33
57.9%
N24
42.1%
Space Separator
ValueCountFrequency (%)
549
100.0%
Other Punctuation
ValueCountFrequency (%)
,57
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2810
82.3%
Common606
 
17.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e374
13.3%
o360
12.8%
a265
 
9.4%
r189
 
6.7%
s188
 
6.7%
i179
 
6.4%
n165
 
5.9%
v156
 
5.6%
c133
 
4.7%
d132
 
4.7%
Other values (13)669
23.8%
Common
ValueCountFrequency (%)
549
90.6%
,57
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII3325
97.3%
None91
 
2.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
549
16.5%
e374
11.2%
o360
10.8%
a265
 
8.0%
r189
 
5.7%
s188
 
5.7%
i179
 
5.4%
n165
 
5.0%
v156
 
4.7%
c133
 
4.0%
Other values (12)767
23.1%
None
ValueCountFrequency (%)
ã38
41.8%
ê33
36.3%
é20
22.0%

desloc
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)11.1%
Missing30
Missing (%)52.6%
Memory size584.0 B
Sim, sempre acontecem longe de onde vivo
13 
Nem sempre, às vezes acontecem na favela onde vivo
10 
Nem sempre, às vezes acontecem fora da favela onde vivo, mas consigo me deslocar até eles

Length

Max length89
Median length50
Mean length50.96296296
Min length40

Characters and Unicode

Total characters1376
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim, sempre acontecem longe de onde vivo
2nd rowNem sempre, às vezes acontecem na favela onde vivo
3rd rowNem sempre, às vezes acontecem na favela onde vivo
4th rowNem sempre, às vezes acontecem na favela onde vivo
5th rowNem sempre, às vezes acontecem fora da favela onde vivo, mas consigo me deslocar até eles

Common Values

ValueCountFrequency (%)
Sim, sempre acontecem longe de onde vivo13
22.8%
Nem sempre, às vezes acontecem na favela onde vivo10
 
17.5%
Nem sempre, às vezes acontecem fora da favela onde vivo, mas consigo me deslocar até eles4
 
7.0%
(Missing)30
52.6%

Length

2022-05-31T15:06:01.836311image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:06:01.957027image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
acontecem27
11.0%
onde27
11.0%
vivo27
11.0%
sempre27
11.0%
favela14
 
5.7%
nem14
 
5.7%
às14
 
5.7%
vezes14
 
5.7%
sim13
 
5.3%
longe13
 
5.3%
Other values (10)55
22.4%

Most occurring characters

ValueCountFrequency (%)
e233
16.9%
218
15.8%
o110
 
8.0%
m89
 
6.5%
a85
 
6.2%
v82
 
6.0%
n81
 
5.9%
s71
 
5.2%
c62
 
4.5%
d48
 
3.5%
Other values (13)297
21.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1100
79.9%
Space Separator218
 
15.8%
Other Punctuation31
 
2.3%
Uppercase Letter27
 
2.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e233
21.2%
o110
10.0%
m89
 
8.1%
a85
 
7.7%
v82
 
7.5%
n81
 
7.4%
s71
 
6.5%
c62
 
5.6%
d48
 
4.4%
i44
 
4.0%
Other values (9)195
17.7%
Uppercase Letter
ValueCountFrequency (%)
N14
51.9%
S13
48.1%
Space Separator
ValueCountFrequency (%)
218
100.0%
Other Punctuation
ValueCountFrequency (%)
,31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1127
81.9%
Common249
 
18.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e233
20.7%
o110
9.8%
m89
 
7.9%
a85
 
7.5%
v82
 
7.3%
n81
 
7.2%
s71
 
6.3%
c62
 
5.5%
d48
 
4.3%
i44
 
3.9%
Other values (11)222
19.7%
Common
ValueCountFrequency (%)
218
87.6%
,31
 
12.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII1358
98.7%
None18
 
1.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e233
17.2%
218
16.1%
o110
 
8.1%
m89
 
6.6%
a85
 
6.3%
v82
 
6.0%
n81
 
6.0%
s71
 
5.2%
c62
 
4.6%
d48
 
3.5%
Other values (11)279
20.5%
None
ValueCountFrequency (%)
à14
77.8%
é4
 
22.2%

evenpub
Categorical

HIGH CORRELATION

Distinct5
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size584.0 B
Não tenho conhecimento
19 
A maioria dos eventos que acesso são promovidos por organizações civis
13 
Não, nunca aconteceu
12 
Sim, aconteceu poucas vezes
10 
Sim, acontecem com frequência

Length

Max length70
Median length29
Mean length33.77192982
Min length20

Characters and Unicode

Total characters1925
Distinct characters28
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowA maioria dos eventos que acesso são promovidos por organizações civis
2nd rowSim, aconteceu poucas vezes
3rd rowSim, aconteceu poucas vezes
4th rowNão tenho conhecimento
5th rowNão tenho conhecimento

Common Values

ValueCountFrequency (%)
Não tenho conhecimento19
33.3%
A maioria dos eventos que acesso são promovidos por organizações civis13
22.8%
Não, nunca aconteceu12
21.1%
Sim, aconteceu poucas vezes10
17.5%
Sim, acontecem com frequência3
 
5.3%

Length

2022-05-31T15:06:02.089654image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:06:02.220303image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não31
 
10.8%
aconteceu22
 
7.6%
conhecimento19
 
6.6%
tenho19
 
6.6%
são13
 
4.5%
sim13
 
4.5%
civis13
 
4.5%
organizações13
 
4.5%
promovidos13
 
4.5%
por13
 
4.5%
Other values (12)119
41.3%

Most occurring characters

ValueCountFrequency (%)
o256
13.3%
231
12.0%
e195
10.1%
c142
 
7.4%
n135
 
7.0%
s124
 
6.4%
a115
 
6.0%
i113
 
5.9%
t76
 
3.9%
m64
 
3.3%
Other values (18)474
24.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1612
83.7%
Space Separator231
 
12.0%
Uppercase Letter57
 
3.0%
Other Punctuation25
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o256
15.9%
e195
12.1%
c142
8.8%
n135
8.4%
s124
 
7.7%
a115
 
7.1%
i113
 
7.0%
t76
 
4.7%
m64
 
4.0%
u60
 
3.7%
Other values (13)332
20.6%
Uppercase Letter
ValueCountFrequency (%)
N31
54.4%
A13
22.8%
S13
22.8%
Space Separator
ValueCountFrequency (%)
231
100.0%
Other Punctuation
ValueCountFrequency (%)
,25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1669
86.7%
Common256
 
13.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o256
15.3%
e195
11.7%
c142
 
8.5%
n135
 
8.1%
s124
 
7.4%
a115
 
6.9%
i113
 
6.8%
t76
 
4.6%
m64
 
3.8%
u60
 
3.6%
Other values (16)389
23.3%
Common
ValueCountFrequency (%)
231
90.2%
,25
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII1852
96.2%
None73
 
3.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o256
13.8%
231
12.5%
e195
10.5%
c142
 
7.7%
n135
 
7.3%
s124
 
6.7%
a115
 
6.2%
i113
 
6.1%
t76
 
4.1%
m64
 
3.5%
Other values (14)401
21.7%
None
ValueCountFrequency (%)
ã44
60.3%
ç13
 
17.8%
õ13
 
17.8%
ê3
 
4.1%

apcult
Categorical

HIGH CORRELATION

Distinct4
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size584.0 B
Não, acredito que não exista
20 
Sim, mas nunca fui
14 
Não sei responder
12 
Sim, e frequento
11 

Length

Max length28
Median length18
Mean length20.9122807
Min length16

Characters and Unicode

Total characters1192
Distinct characters21
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão sei responder
2nd rowSim, e frequento
3rd rowSim, mas nunca fui
4th rowNão sei responder
5th rowNão sei responder

Common Values

ValueCountFrequency (%)
Não, acredito que não exista20
35.1%
Sim, mas nunca fui14
24.6%
Não sei responder12
21.1%
Sim, e frequento11
19.3%

Length

2022-05-31T15:06:02.394838image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:06:02.578345image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não52
23.1%
sim25
11.1%
acredito20
 
8.9%
que20
 
8.9%
exista20
 
8.9%
mas14
 
6.2%
nunca14
 
6.2%
fui14
 
6.2%
sei12
 
5.3%
responder12
 
5.3%
Other values (2)22
9.8%

Most occurring characters

ValueCountFrequency (%)
168
14.1%
e129
 
10.8%
o95
 
8.0%
i91
 
7.6%
n71
 
6.0%
a68
 
5.7%
u59
 
4.9%
s58
 
4.9%
r55
 
4.6%
ã52
 
4.4%
Other values (11)346
29.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter922
77.3%
Space Separator168
 
14.1%
Uppercase Letter57
 
4.8%
Other Punctuation45
 
3.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e129
14.0%
o95
10.3%
i91
9.9%
n71
 
7.7%
a68
 
7.4%
u59
 
6.4%
s58
 
6.3%
r55
 
6.0%
ã52
 
5.6%
t51
 
5.5%
Other values (7)193
20.9%
Uppercase Letter
ValueCountFrequency (%)
N32
56.1%
S25
43.9%
Space Separator
ValueCountFrequency (%)
168
100.0%
Other Punctuation
ValueCountFrequency (%)
,45
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin979
82.1%
Common213
 
17.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e129
13.2%
o95
 
9.7%
i91
 
9.3%
n71
 
7.3%
a68
 
6.9%
u59
 
6.0%
s58
 
5.9%
r55
 
5.6%
ã52
 
5.3%
t51
 
5.2%
Other values (9)250
25.5%
Common
ValueCountFrequency (%)
168
78.9%
,45
 
21.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII1140
95.6%
None52
 
4.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
168
14.7%
e129
11.3%
o95
 
8.3%
i91
 
8.0%
n71
 
6.2%
a68
 
6.0%
u59
 
5.2%
s58
 
5.1%
r55
 
4.8%
t51
 
4.5%
Other values (10)295
25.9%
None
ValueCountFrequency (%)
ã52
100.0%

projpub
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)5.4%
Missing1
Missing (%)1.8%
Memory size584.0 B
Não conheço nenhum
40 
Sim, mas poucos
13 
Sim, conheço vários
 
3

Length

Max length19
Median length18
Mean length17.35714286
Min length15

Characters and Unicode

Total characters972
Distinct characters20
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão conheço nenhum
2nd rowNão conheço nenhum
3rd rowSim, mas poucos
4th rowNão conheço nenhum
5th rowNão conheço nenhum

Common Values

ValueCountFrequency (%)
Não conheço nenhum40
70.2%
Sim, mas poucos13
 
22.8%
Sim, conheço vários3
 
5.3%
(Missing)1
 
1.8%

Length

2022-05-31T15:06:02.725953image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:06:02.876590image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
conheço43
25.6%
não40
23.8%
nenhum40
23.8%
sim16
 
9.5%
mas13
 
7.7%
poucos13
 
7.7%
vários3
 
1.8%

Most occurring characters

ValueCountFrequency (%)
o155
15.9%
n123
12.7%
112
11.5%
h83
8.5%
e83
8.5%
m69
7.1%
c56
 
5.8%
u53
 
5.5%
ç43
 
4.4%
ã40
 
4.1%
Other values (10)155
15.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter788
81.1%
Space Separator112
 
11.5%
Uppercase Letter56
 
5.8%
Other Punctuation16
 
1.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o155
19.7%
n123
15.6%
h83
10.5%
e83
10.5%
m69
8.8%
c56
 
7.1%
u53
 
6.7%
ç43
 
5.5%
ã40
 
5.1%
s29
 
3.7%
Other values (6)54
 
6.9%
Uppercase Letter
ValueCountFrequency (%)
N40
71.4%
S16
 
28.6%
Space Separator
ValueCountFrequency (%)
112
100.0%
Other Punctuation
ValueCountFrequency (%)
,16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin844
86.8%
Common128
 
13.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
o155
18.4%
n123
14.6%
h83
9.8%
e83
9.8%
m69
8.2%
c56
 
6.6%
u53
 
6.3%
ç43
 
5.1%
ã40
 
4.7%
N40
 
4.7%
Other values (8)99
11.7%
Common
ValueCountFrequency (%)
112
87.5%
,16
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII886
91.2%
None86
 
8.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o155
17.5%
n123
13.9%
112
12.6%
h83
9.4%
e83
9.4%
m69
7.8%
c56
 
6.3%
u53
 
6.0%
N40
 
4.5%
s29
 
3.3%
Other values (7)83
9.4%
None
ValueCountFrequency (%)
ç43
50.0%
ã40
46.5%
á3
 
3.5%

projart
Categorical

HIGH CORRELATION

Distinct4
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size584.0 B
Não
20 
Sim
20 
Não sei
16 
Sim, e participo
 
1

Length

Max length16
Median length3
Mean length4.350877193
Min length3

Characters and Unicode

Total characters248
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.8%

Sample

1st rowNão
2nd rowNão
3rd rowNão
4th rowNão sei
5th rowNão sei

Common Values

ValueCountFrequency (%)
Não20
35.1%
Sim20
35.1%
Não sei16
28.1%
Sim, e participo1
 
1.8%

Length

2022-05-31T15:06:03.020210image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-31T15:06:03.151813image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
não36
48.0%
sim21
28.0%
sei16
21.3%
e1
 
1.3%
participo1
 
1.3%

Most occurring characters

ValueCountFrequency (%)
i39
15.7%
o37
14.9%
N36
14.5%
ã36
14.5%
S21
8.5%
m21
8.5%
18
7.3%
e17
6.9%
s16
6.5%
p2
 
0.8%
Other values (5)5
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter172
69.4%
Uppercase Letter57
 
23.0%
Space Separator18
 
7.3%
Other Punctuation1
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i39
22.7%
o37
21.5%
ã36
20.9%
m21
12.2%
e17
9.9%
s16
9.3%
p2
 
1.2%
a1
 
0.6%
r1
 
0.6%
t1
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
N36
63.2%
S21
36.8%
Space Separator
ValueCountFrequency (%)
18
100.0%
Other Punctuation
ValueCountFrequency (%)
,1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin229
92.3%
Common19
 
7.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
i39
17.0%
o37
16.2%
N36
15.7%
ã36
15.7%
S21
9.2%
m21
9.2%
e17
7.4%
s16
7.0%
p2
 
0.9%
a1
 
0.4%
Other values (3)3
 
1.3%
Common
ValueCountFrequency (%)
18
94.7%
,1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII212
85.5%
None36
 
14.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i39
18.4%
o37
17.5%
N36
17.0%
S21
9.9%
m21
9.9%
18
8.5%
e17
8.0%
s16
7.5%
p2
 
0.9%
,1
 
0.5%
Other values (4)4
 
1.9%
None
ValueCountFrequency (%)
ã36
100.0%

inters
Categorical

HIGH CORRELATION
MISSING

Distinct37
Distinct (%)66.1%
Missing1
Missing (%)1.8%
Memory size584.0 B
Não tenho interesse
Dança (passinho, samba, etc)
Dança (passinho, samba, etc) Música (cantor, produtor, instrumentista, etc) Teatro Fotografia
 
3
Artes visuais (pintura, escultura, etc) Música (cantor, produtor, instrumentista, etc) Teatro Fotografia Literatura/escrita
 
2
Dança (passinho, samba, etc) Artes visuais (pintura, escultura, etc) Indumentária (desenho e/ou confecção de roupas) Música (cantor, produtor, instrumentista, etc) Teatro Fotografia Literatura/escrita
 
2
Other values (32)
34 

Length

Max length200
Median length133
Mean length72.71428571
Min length17

Characters and Unicode

Total characters4072
Distinct characters36
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)53.6%

Sample

1st rowArtes visuais (pintura, escultura, etc) Música (cantor, produtor, instrumentista, etc) Teatro Fotografia Literatura/escrita
2nd rowIndumentária (desenho e/ou confecção de roupas) Literatura/escrita
3rd rowArtes visuais (pintura, escultura, etc) Teatro
4th rowNão tenho interesse
5th rowDança (passinho, samba, etc)

Common Values

ValueCountFrequency (%)
Não tenho interesse8
 
14.0%
Dança (passinho, samba, etc)7
 
12.3%
Dança (passinho, samba, etc) Música (cantor, produtor, instrumentista, etc) Teatro Fotografia3
 
5.3%
Artes visuais (pintura, escultura, etc) Música (cantor, produtor, instrumentista, etc) Teatro Fotografia Literatura/escrita2
 
3.5%
Dança (passinho, samba, etc) Artes visuais (pintura, escultura, etc) Indumentária (desenho e/ou confecção de roupas) Música (cantor, produtor, instrumentista, etc) Teatro Fotografia Literatura/escrita2
 
3.5%
Dança (passinho, samba, etc) Artes visuais (pintura, escultura, etc)2
 
3.5%
Teatro Fotografia2
 
3.5%
Indumentária (desenho e/ou confecção de roupas)1
 
1.8%
Dança (passinho, samba, etc) Música (cantor, produtor, instrumentista, etc) Fotografia Literatura/escrita1
 
1.8%
Artes visuais (pintura, escultura, etc) Indumentária (desenho e/ou confecção de roupas) Fotografia Literatura/escrita1
 
1.8%
Other values (27)27
47.4%

Length

2022-05-31T15:06:03.315375image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
etc66
 
13.8%
dança27
 
5.6%
passinho27
 
5.6%
samba27
 
5.6%
fotografia26
 
5.4%
teatro22
 
4.6%
literatura/escrita20
 
4.2%
escultura20
 
4.2%
pintura20
 
4.2%
visuais20
 
4.2%
Other values (14)204
42.6%

Most occurring characters

ValueCountFrequency (%)
423
 
10.4%
a414
 
10.2%
t359
 
8.8%
e303
 
7.4%
s282
 
6.9%
r280
 
6.9%
o244
 
6.0%
i232
 
5.7%
n203
 
5.0%
u180
 
4.4%
Other values (26)1152
28.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3148
77.3%
Space Separator423
 
10.4%
Other Punctuation185
 
4.5%
Uppercase Letter156
 
3.8%
Close Punctuation80
 
2.0%
Open Punctuation80
 
2.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a414
13.2%
t359
11.4%
e303
9.6%
s282
9.0%
r280
8.9%
o244
7.8%
i232
7.4%
n203
6.4%
u180
 
5.7%
c172
 
5.5%
Other values (13)479
15.2%
Uppercase Letter
ValueCountFrequency (%)
D27
17.3%
F26
16.7%
T22
14.1%
A20
12.8%
L20
12.8%
M19
12.2%
I14
9.0%
N8
 
5.1%
Other Punctuation
ValueCountFrequency (%)
,151
81.6%
/34
 
18.4%
Space Separator
ValueCountFrequency (%)
423
100.0%
Close Punctuation
ValueCountFrequency (%)
)80
100.0%
Open Punctuation
ValueCountFrequency (%)
(80
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3304
81.1%
Common768
 
18.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a414
12.5%
t359
10.9%
e303
9.2%
s282
8.5%
r280
8.5%
o244
 
7.4%
i232
 
7.0%
n203
 
6.1%
u180
 
5.4%
c172
 
5.2%
Other values (21)635
19.2%
Common
ValueCountFrequency (%)
423
55.1%
,151
 
19.7%
)80
 
10.4%
(80
 
10.4%
/34
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII3976
97.6%
None96
 
2.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
423
10.6%
a414
 
10.4%
t359
 
9.0%
e303
 
7.6%
s282
 
7.1%
r280
 
7.0%
o244
 
6.1%
i232
 
5.8%
n203
 
5.1%
u180
 
4.5%
Other values (22)1056
26.6%
None
ValueCountFrequency (%)
ç41
42.7%
ã22
22.9%
ú19
19.8%
á14
 
14.6%

progress
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing57
Missing (%)100.0%
Memory size584.0 B

Interactions

2022-05-31T15:04:56.744331image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-31T15:04:56.438662image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-31T15:04:56.868001image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-05-31T15:04:56.622657image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Correlations

2022-05-31T15:06:03.493896image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-05-31T15:06:03.740236image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-05-31T15:06:03.928733image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-05-31T15:06:05.378854image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-05-31T15:04:57.807533image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-05-31T15:05:03.754295image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-05-31T15:05:17.847087image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

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0BissexualNenhumaNãoNegra22.0Não moro em comunidadeNãoNaNEnsino superior incompletoCertidão de Nascimento Carteira de Identidade (RG) CPF Carteira de Trabalho Título de EleitorSimNaNRio de JaneiroNaNNãoNaNSimNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNCom frequênciaNUNCA fui abordada de acordo com minha identidade de gêneroSimNãoSim, na zona norte do Rio de JaneiroSimSimNãoSimNão, nunca aconteceuNão, nunca aconteceuNãoNãoNaNCristãNada próximaSimSimSimSimSim, dentro da minha casa ou de parentesSimTenho um plano residencial de internetSimInstagram Whatsapp Twitter Tinder, grindr outros apps de paqueraTrabalho Estudo Ativismo Lazer Grupos de apoio Se informar Conhecer gente nova Flertes/relacionamentoRacismo A plataforma que utilizo não contempla minha identidade de gêneroPost removido Palavras censuradas (ex. nao consigo postar a palavra “sapatao” no insta)Sim, antes e durante a pandemiaDocumentos (título de eleitor, cpf, rg) Certificados diversos (antecedentes criminais, cadastro positivo etc)Dificuldade em encontrar informações corretas nos sites e em buscasNãoNãoQuase nunca vouVou com frequênciaNãoSim, leio com frequência a livros, revistas digitais e/ou artigos onlineExtremamente importanteSim, participo com frequência de eventos dentro e fora da favela onde vivoSim, sempre acontecem longe de onde vivoA maioria dos eventos que acesso são promovidos por organizações civisNão sei responderNão conheço nenhumNãoArtes visuais (pintura, escultura, etc) Música (cantor, produtor, instrumentista, etc) Teatro Fotografia Literatura/escritaNaN
1HeterossexualTravestiNãoNegra21.0Não moro em comunidadeNãoNaNEnsino superior incompletoCertidão de Nascimento Carteira de Identidade (RG) CPF Carteira de Trabalho Título de EleitorSimNaNSergipeNaNNãoNaNNãoNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNãoNaNNaNNaNNaNNaNNaNNãoNãoNão, nunca aconteceuNão, nunca aconteceuNãoNãoNaNEvangélicaNada próximaSimNãoNãoNãoNãoNãoTenho um plano residencial de internetSimInstagram Whatsapp Tiktok Twitter Tinder, grindr outros apps de paqueraTrabalho Estudo Ativismo Lazer Se informar Conhecer gente nova Conectar com a família Fazer compras Acesso a serviços Flertes/relacionamentoRacismo LGBTfobia Machismo Xingamentos e/ou humilhaçõesNunca tive esse tipo de problemasNunca preciseiNaNNaNNãoNãoQuase nunca vouQuase nunca vouSim, e frequentoSim, leio com frequência a livros, revistas digitais e/ou artigos onlineExtremamente importanteSim, participo com frequência apenas de eventos dentro da favela onde vivoNaNSim, aconteceu poucas vezesSim, e frequentoNão conheço nenhumNãoIndumentária (desenho e/ou confecção de roupas) Literatura/escritaNaN
2BissexualTravestiNãoNegra20.0RocinhaNãoNaNCursos profissionalizantes ou de capacitaçãoCertidão de Nascimento Carteira de Identidade (RG)SimNaNRio de JaneiroNaNNãoNaNNãoMoro com mais que cinco pessoasFamíliaEu mesma contei8.0Me apoiaram/acolheramBoaSim depende financeiramente e de cuidadosNãoNãoNão e, não pretendo terNenhuma das opções acimaNaNNão se aplicaMora de favorGeladeira Fogão CelularDurmo num cômodo sozinho em cama/colchão/outros sozinhoPosto de atendimento médicoTerra/chão batidoEspaço culturalNãoNunca trabalheiNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNão, parei/desisti por outros motivosPúblicaNão oferece materiais gratuitosNa mesma comunidade em que vivo, porém distanteNaNNaNExpulsão da escolaSimRacismoSim, sofri/sofro algumas vezesPor parte dos alunosNaNNaNSim, vários(as)NãoNãoNão sei o que éNãoNãoNãoNaNVou mais de duas vezes ao anoVou mais de duas vezes ao anoSimNegativoPrefiro não responderNaNNãoNaNNãoNaNNãoNaNNaNNãoSó às vezes, raramente.SimMaconhaNaNSim, e frequento(ei) por vontade própriaSimSimSim, mas o serviço é ruim, quase nunca tem medicamentosSim, e já estou imunizadaGripe Sarampo Febre Amarela Tríplice Viral Sífilis HPV Não sei/ não lembroNão possuoNão seiSim, pelo menos duas vezes ao diaSim, uma vezNão utilizoNão consegui realizar meu cadastroSimLeve, com pouco sintomasSim, por amigos ou familiares Fiz tratamento precoce por conta própriaNãoNaNNãoNaNSimNo shoppingNaNNaNNãoNãoNão tenho certeza/Não percebiSim, uma vezSim, uma vezNãoFica longe da minha casa (acesso)Agente público da educação (professor/a, diretor/a, coordenador pedagógico, etc) Homem na ruaFisicamente, com uma madeira ou objeto VirtualmenteEra um homem negro/pardo Não sei dizerSim, depois dos meus 18 anos.NUNCA fui abordada de acordo com minha identidade de gêneroPrefiro não responderSimNão me lembroNãoNãoNãoNãoNão, nunca aconteceuSim, várias vezesNãoNãoNaNMinha umbanda de axé ❤PraticanteNãoPrefiro não responderNãoNãoSim, na escolaNão seiInternet por redes de vizinhosSimFacebook WhatsappLazer Conectar com a famíliaRacismo Intolerância religiosa Xingamentos e/ou humilhaçõesNunca tive esse tipo de problemasNão tenho certezaNaNNaNNãoDepende da situaçãoNunca fuiQuase nunca vouSim, mas não frequentoSim, mas leio com pouca frequênciaNada importanteNão, os ingressos para esses eventos são carosNaNSim, aconteceu poucas vezesSim, mas nunca fuiSim, mas poucosNãoArtes visuais (pintura, escultura, etc) TeatroNaN
3HeterossexualMulher transNãoNegra26.0RocinhaNão tenho certezaNaNEnsino fundamental incompletoCertidão de Nascimento Carteira de Identidade (RG) CPF Título de EleitorNãoCarteira de Trabalho Título de EleitorCearáNaNNãoNaNNãoMoro com uma pessoaAmigosEu mesma contei10.0Meus pais não me acolheram mas outras pessoas da família simBoaNão, não sou responsável por ninguém em meu ambiente domiciliarSimNão seiNão, mas quero terCasa toda de tijolo e cimento (alvenaria)NaNBanheiro com ligação à rede de esgoto Caixa d’agua ou cisterna Energia elétrica da rede de abastecimento (regularizada)Paga aluguelFogão CelularDurmo num cômodo sozinho em cama/colchão/outros sozinhoNão sei dizerRua asfaltadaPraça pública Quadra de futebol Quadra poliesportiva Espaço cultural Parque infantil Parque arborizado Centro comunitário Espaço de eventos e lazer Bailes e fluxos (funk, forró, reggae, rap, rock etc)NãoEstou desempregadoNão, mas trabalho longeProfissional do sexoSimAté 99 reaisSim, em partesNãoSimNaNNão, nunca sofri nenhum tipo de assédio no trabalhonão, nunca sofrinão, nunca sofriSimNãonão seiNãoNão, porque fui recusadaNão, parei/desisti por outros motivosPúblicaSim, oferece livros didáticos Sim, oferece cadernos, lápis, canetas… Sim, oferece uniformePerto, na mesma comunidade em que vivoNaNNaNExpulsão da escolaNãoNaNNunca sofri/sofroNão consigo definirNaNNaNSim, apenas um(a) ou poucosNãoNãoNão sei o que éNãoNãoNãoNaNVou mais de duas vezes ao anoNunca vouSimNegativoSimNegativoSimNegativoSimNegativoNãoNaNNaNSimSimNãoMaconhaO serviço é limitadoNãoNão seiNão seiNão seiSim, e já estou imunizadaNão sei/ não lembroNão possuoNão seiSim, pelo menos duas vezes ao diaSim, inúmeras vezesNão utilizoOs serviços são ruinsNãoNaNNãoSimLGBTfobiaSim, mais de uma vezNa comunidade onde vivoSimNa escola/universidade FestasNão, nunca.NaNNãoNãoSim, inúmeras vezesSim, uma vezNãoNãoNaNHomem da minha comunidadeFisicamente, com tapas, chutes, soco e pontapésEra um homem negro/pardoSim, antes e depois dos meus 18 anos.NUNCA fui abordada de acordo com minha identidade de gêneroNaNSimNaNSimSimSimNãoNão, nunca aconteceuSim, com frequênciaSimNãoNaNWiccaPouco próximaNãoNãoNãoNãoNãoNãoCelular pré-pago (dados limitados + aplicativos)SimInstagram Facebook Whatsapp TwitterTrabalho Estudo LazerLGBTfobiaPost removido Conta bloqueada/excluídaSim, durante a pandemiaAuxílio emergencial / cadastro únicoDificuldade em acessar a internetNãoDepende da situaçãoQuase nunca vouNunca fuiSim, mas não frequentoNão, não tenho esse costumeNada importanteNão, é caro me locomover até elesNaNNão tenho conhecimentoNão sei responderNão conheço nenhumNão seiNão tenho interesseNaN
4HeterossexualMulher transNãoNegra18.0RocinhaNãoNaNEnsino médio completoCertidão de Nascimento Carteira de Identidade (RG) CPF Carteira de TrabalhoSimNaNRio de JaneiroNaNNãoNaNNãoMoro com quatro pessoasFamíliaDe outras maneiras10.0Me apoiaram/acolheram Minha mãe me acolheu e meu pai nãoBoaNão, não sou responsável por ninguém em meu ambiente domiciliarNão sei especificarNãoNão, mas quero terCasa toda de tijolo e cimento (alvenaria)NaNÁgua encanada ligada ao sistema de fornecimento público de água Energia elétrica da rede de abastecimento (irregular)Casa própriaGeladeira Fogão Microondas Televisão Máquina de lavar roupaDurmo num cômodo com mais pessoas e divido cama/colchão/outrosEscola/creche pública Escola/creche privadaRua de pedraPraça pública Quadra de futebol Quadra poliesportiva Parque infantil Bailes e fluxos (funk, forró, reggae, rap, rock etc)NãoNunca trabalheiNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNão, já concluí meus estudosPúblicaSim, oferece livros didáticos Sim, oferece cadernos, lápis, canetas… Sim, oferece uniformeFora da comunidade onde vivoNaNNaNNaNSimPela minha orientação sexualSim, sofri/sofro poucas vezesPor parte dos alunosNaNNaNSim, apenas um(a) ou poucosSim, apenas um(a) ou poucosNãonãoSimNãoNãoNaNVou mais de duas vezes ao anoRaramente vouSimNegativoSimNegativoNãoNaNSimNegativoNãoNaNNaNNãoSimSimMaconhaNaNNãoNão seiNão seiSim, mas o serviço é ruim, quase nunca tem medicamentosSim, e já estou imunizadaNão sei/ não lembroNão possuoNão possuo nenhum diagnósticoSim, três ou mais vezes ao diaNão seiSim, ocasionalmenteNaNNãoNaNNãoNão percebi ou não tenho certezaNaNNãoNaNSimNa escola/universidadeNão, nunca.NaNNãoNãoSim, inúmeras vezesSim, inúmeras vezesNão tenho certeza/Não percebiNãoNão acredito que esse tipo de serviço funcione (credibilidade)Homem da minha comunidade Homem na ruaVerbalmente/ com xingamentosEra um homem branco Era um homem negro/pardoSim, depois dos meus 18 anos.ALGUMAS vezes fui abordada de acordo com minha identidade de gêneroSimNãoSim, na zona sul do Rio de JaneiroNãoNãoNãoNãoNão, nunca aconteceuNão, nunca aconteceuNãoNãoNaNCatólicaNada próximaNãoNãoSimSimNão seiNão seiInternet por redes de vizinhos Por pontos de wi-fi abertos pela cidade (internet provida por governo/empresas)SimInstagram Facebook Whatsapp Tiktok Twitter Tinder, grindr outros apps de paquera TelegramEstudo Lazer Se informar Conhecer gente nova Fazer compras Flertes/relacionamentoMachismo Assédio sexualConta bloqueada/excluídaSim, durante a pandemiaEstudos durante a pandemiaDificuldade em encontrar informações corretas nos sites e em buscasSimSimQuase nunca vouQuase nunca vouSim, mas não frequentoSim, mas leio com pouca frequênciaImportanteNão, os ingressos para esses eventos são carosNaNNão tenho conhecimentoNão sei responderNão conheço nenhumNão seiDança (passinho, samba, etc)NaN
5HeterossexualMulher transNãoNegra28.0RocinhaNãoNaNEnsino médio incompletoCertidão de Nascimento Carteira de Identidade (RG) CPF Carteira de Trabalho Título de EleitorSimNaNRio de JaneiroNaNNãoNaNNãoMoro com quatro pessoasFamíliaEu mesma contei15.0Me apoiaram/acolheramBoaNão, não sou responsável por ninguém em meu ambiente domiciliarNãoNãoNão e, não pretendo terCasa toda de tijolo e cimento (alvenaria)NaNÁgua encanada ligada ao sistema de fornecimento público de águaCasa própriaGeladeira Fogão Televisão Máquina de lavar roupa Celular RádioDurmo num cômodo sozinho em cama/colchão/outros sozinhoFornecimento de energia elétrica Água encanadaRua asfaltadaPraça pública Quadra de futebol Espaço cultural Parque infantil Parque arborizado Centro comunitário Espaço de eventos e lazer Bailes e fluxos (funk, forró, reggae, rap, rock etc)NãoEstou empregadoSimCabeleireiraSimAté 99 reaisSim, em partesNãoSimNaNNão, nunca sofri nenhum tipo de assédio no trabalhonão, nunca sofrinão, nunca sofriNão, porque não me enquadrei nos requisitosNãonãoNãoSimSimPúblicaSim, oferece livros didáticos Sim, oferece cadernos, lápis, canetas… Sim, oferece uniformeFora da comunidade onde vivoÔnibusA escola/universidade não ofereceu aulas remotasNaNNãoNaNNunca sofri/sofroNaNSimNãoSim, vários(as)NãoNãosim, uso atualmenteSimNãoNãoNaNRaramente vouRaramente vouSimNegativoSimNegativoSimNegativoSimNegativoNãoNaNNaNNãoSimSimNunca utilizei nenhuma dessas substânciasNaNNãoSimSimSim, e o serviço é bomSim, e já estou imunizadaNão sei/ não lembroNão possuoNão possuo nenhum diagnósticoSim, pelo menos duas vezes ao diaNão seiSim, regularmenteNaNNãoNaNNãoNãoNaNNãoNaNNãoNaNNão, nunca.NaNPrefiro não responderNãoSim, inúmeras vezesSim, inúmeras vezesSim, inúmeras vezesNãoPrefiro não dizerNaNNaNNaNSim, depois dos meus 18 anos.SEMPRE fui abordada de acordo com minha identidade de gêneroNãoNãoSim, na zona norte do Rio de JaneiroNãoNãoNãoNãoSim, poucas vezesSim, várias vezesNãoSimUmbandistasNão fui criada em nenhuma crença religiosaNada próximaNãoNãoNãoNãoNãoPrefiro não responderPor pontos de wi-fi abertos pela cidade (internet provida por governo/empresas) Tenho um plano residencial de internetSimInstagram Facebook Whatsapp Tiktok TelegramTrabalho Estudo LazerRacismoNunca tive esse tipo de problemasNunca preciseiNaNNaNNãoDepende da situaçãoQuase nunca vouQuase nunca vouSim, mas não frequentoNão, não tenho esse costumeImportanteSim, participo com frequência de eventos dentro e fora da favela onde vivoNem sempre, às vezes acontecem na favela onde vivoNão tenho conhecimentoNão, acredito que não existaNão conheço nenhumNãoDança (passinho, samba, etc) Teatro FotografiaNaN
6HeterossexualMulher transNãoNegra27.0RocinhaNãoNaNEnsino médio completoCertidão de Nascimento Carteira de Identidade (RG) CPFSimNaNRio de JaneiroNaNNãoNaNNãoMoro com quatro pessoasFamíliaEu mesma contei18.0Me apoiaram/acolheramBoaNão, não sou responsável por ninguém em meu ambiente domiciliarNãoSimNão, mas quero terCasa toda de tijolo e cimento (alvenaria)NaNEnergia elétrica da rede de abastecimento (irregular)Casa própriaComputador Geladeira Fogão Microondas Televisão Ar condicionado Máquina de lavar roupa Celular RádioDurmo num cômodo com mais pessoas, porém em uma cama/colchão/outros só minhaSistema de esgoto Coleta de lixoRua asfaltadaPraça pública Quadra de futebol Espaço cultural Parque infantil Bailes e fluxos (funk, forró, reggae, rap, rock etc)NãoEstou desempregadoSimCabeleireiraNãoDe 500 a 1.099 reaisSim, completamenteNãoSimNaNNão, nunca sofri nenhum tipo de assédio no trabalhonão, nunca sofrinão, nunca sofriNão soliciteiNãonãoNãoNão, porque fui recusadaNão, já concluí meus estudosPúblicaSim, oferece cadernos, lápis, canetas…Perto, na mesma comunidade em que vivoNaNNaNNaNNãoNaNNunca sofri/sofroNão consigo definirNaNNaNSim, vários(as)Sim, apenas um(a) ou poucosNãoNão sei o que éNãoNãoNãoNaNRaramente vouPelo menos uma ou duas vezes ao anoSimNegativoNãoNaNNãoNaNNãoNaNSimPara terapia hormonal (mudanças corporais)SimNãoNãoSimNunca utilizei nenhuma dessas substânciasNaNNãoSimNão seiSim, mas o serviço é ruim, quase nunca tem medicamentosSim, e já estou imunizadaNão sei/ não lembroNão possuoNão possuo nenhum diagnósticoSim, três ou mais vezes ao diaNão seiSim, ocasionalmenteNaNNãoNaNNãoNãoNaNNãoNaNNãoNaNNão, nunca.NaNSim, uma vezNãoNão tenho certeza/Não percebiSim, inúmeras vezesSim, inúmeras vezesNãoTenho medo de represálias (segurança pessoal)Sofri uma agressão virtual por desconhecido/ perfil fakeVirtualmenteEra um homem negro/pardoSim, antes dos meus 18 anos.SEMPRE fui abordada de acordo com minha identidade de gêneroNãoNãoSim, na zona norte do Rio de JaneiroNãoNãoNãoNãoNão, nunca aconteceuNão, nunca aconteceuNãoSimCatólicaCatólicaPouco próximaSimSimSimSimNãoNãoTenho um plano residencial de internetSimInstagram Facebook Whatsapp Tiktok Twitter Tinder, grindr outros apps de paqueraConhecer gente novaLGBTfobia Preconceito de classe socialNunca tive esse tipo de problemasNunca preciseiNaNNaNSimNãoQuase nunca vouQuase nunca vouNãoSim, mas leio com pouca frequênciaPouco importanteSim, participo com frequência apenas de eventos dentro da favela onde vivoNaNSim, acontecem com frequênciaSim, e frequentoNão conheço nenhumNão seiNão tenho interesseNaN
7HeterossexualMulher transNãoNegra34.0RocinhaNãoNaNEnsino médio incompletoCertidão de Nascimento Carteira de Identidade (RG) CPF Carteira de Trabalho Título de EleitorNãoCertidão de Nascimento Carteira de Trabalho Título de EleitorRio de JaneiroNaNNãoNaNNãoMoro sozinhaNaNEu mesma contei14.0Me levaram para igreja/rezaram Ficaram preocupados com a violência Minha mãe me acolheu e meu pai nãoBoaSim, depende de meus cuidados, porém não financeirosSimSimSim, filha(s) adotadasCasa toda de tijolo e cimento (alvenaria)NaNÁgua encanada ligada ao sistema de fornecimento público de água Banheiro com ligação à rede de esgoto Caixa d’agua ou cisterna Energia elétrica da rede de abastecimento (irregular)Mora de favorGeladeira Fogão Televisão Celular RádioDurmo num cômodo sozinho em cama/colchão/outros sozinhoFornecimento de energia elétrica Água encanada Escola/creche pública Escola/creche privadaRua asfaltadaPraça pública Quadra de futebol Centro comunitário Espaço de eventos e lazer Bailes e fluxos (funk, forró, reggae, rap, rock etc)SimEstou desempregadoNão, mas trabalho longeServiços geraisSimAté 99 reaisSim, em partesNaNSimNaNSim, assédio moral Sim, assédio sexual Sim, assédio psicológicosim, mais de uma vez/ regularmentesim, mais de uma vez/ regularmenteNão sei como devo fazer para acessarSimsimNaNSimNão, parei/desisti por outros motivosPúblicaSim, oferece livros didáticosFora da comunidade onde vivoNaNNaNViolências sofridos no âmbito escolarSimViolência de gênero/identidade de gênero Pela minha orientação sexualSim, sofri/sofro algumas vezesPor parte dos alunosNaNNaNSim, apenas um(a) ou poucosNãoNãonãoSimSimSimNaNVou mais de duas vezes ao anoPelo menos uma ou duas vezes ao anoSimPositivoSimPositivoSimNegativoPrefiro não responderNaNSimPara aceleração metabólica (ganho muscular, uso dietário)NãoSimSimSimMaconha CocaínaNaNSim, e frequento(ei) por vontade própriaSimSimSim, e o serviço é bomSim, e já estou imunizadaNão sei/ não lembroNão possuoSim, mas não possuo laudoSim, uma vez ao diaSim, uma vezSim, regularmenteNaNNãoNaNSim, por amigos ou familiaresNãoNaNSim, mais de uma vezNa comunidade onde vivo Na escola/universidade No trabalho No ambiente familiarNãoNaNNão, nunca.NaNSim, uma vezNãoSim, inúmeras vezesSim, inúmeras vezesSim, inúmeras vezesNãoNão acredito que esse tipo de serviço funcione (credibilidade)Agente público de segurança (policial militar, civil, guarda municipal, polícia federal etc) Homem da minha comunidade Mulher da minha comunidade Homem na ruaVerbalmente/ com xingamentos Fisicamente, com tapas, chutes, soco e pontapésEra um homem negro/pardoCom frequênciaPOUCAS vezes fui abordada de acordo com minha identidade de gêneroSimSimSim, na zona sul do Rio de JaneiroPrefiro não responderSimSimSimSim, poucas vezesSim, várias vezesPrefiro não responderSimCatólicaCatólicaPraticanteSimSimSimSimSim, dentro da minha casa ou de parentesNão seiCelular pré-pago (dados limitados + aplicativos) Por pontos de wi-fi abertos pela cidade (internet provida por governo/empresas)SimInstagram Facebook WhatsappTrabalhoLGBTfobiaPost removido Conta bloqueada/excluídaSim, durante a pandemiaAuxílio emergencial / cadastro únicoDificuldade em acessar a internetNãoNãoQuase nunca vouQuase nunca vouSim, mas não frequentoSim, mas leio com pouca frequênciaImportanteSim, participo com frequência de eventos dentro e fora da favela onde vivoNem sempre, às vezes acontecem na favela onde vivoNão tenho conhecimentoNão sei responderSim, mas poucosSimDança (passinho, samba, etc) Música (cantor, produtor, instrumentista, etc) Teatro FotografiaNaN
8HeterossexualTravestiNãoNegra26.0RocinhaNãoNaNEnsino fundamental incompletoCertidão de Nascimento Carteira de Identidade (RG) CPF Carteira de Trabalho Título de EleitorSimNaNRio de JaneiroNaNNãoNaNNãoMoro com quatro pessoasFamíliaEu mesma contei12.0Me apoiaram/acolheram Não falaram nadaIndiferenteNão, não sou responsável por ninguém em meu ambiente domiciliarNãoSimNão e, não pretendo terCasa toda de tijolo e cimento (alvenaria)NaNÁgua encanada ligada ao sistema de fornecimento público de água Banheiro com ligação à rede de esgoto Caixa d’agua ou cisterna Energia elétrica da rede de abastecimento (irregular)Paga aluguelGeladeira Fogão Televisão Máquina de lavar roupa CelularDurmo num cômodo com mais pessoas, porém em uma cama/colchão/outros só minhaFornecimento de energia elétrica Água encanada Sistema de esgoto Coleta de lixo Escola/creche pública Escola/creche privada Posto de atendimento médicoRua asfaltadaPraça pública Quadra de futebol Quadra poliesportiva Espaço cultural Parque infantil Parque arborizado Centro comunitário Espaço de eventos e lazer Bailes e fluxos (funk, forró, reggae, rap, rock etc)NãoEstou desempregadoNaNBarreira e implantistaSimDe 100 a 499 reaisSim, em partesNaNSimNaNNão, nunca sofri nenhum tipo de assédio no trabalhonão, nunca sofrinão, nunca sofriSimNãonãoNãoSimNão, parei/desisti por vontade própriaPúblicaNão oferece materiais gratuitosPerto, na mesma comunidade em que vivoNaNNaNNaNSimPor conta do nomeNunca sofri/sofroNaNNaNNaNNãoNãoNãosim, já utilizeiSimNãoNãoNaNRaramente vouPelo menos uma ou duas vezes ao anoSimNegativoSimPositivoSimNegativoNãoNaNNãoNaNNaNNãoSimNãoMaconha Cocaína CrackNaNSim, e frequento(ei) por vontade própriaNão seiNão seiNão seiSim, e já estou imunizadaHepatite B e C Sarampo Poliomielite Febre Amarela Tríplice Viral Sífilis Dupla-Tétano Triplice Bacteriana-dTpaNão possuoNão, mas tenho autodiagnostico ou suspeitaSim, três ou mais vezes ao diaNão seiNão utilizoNaNNãoNaNFiz tratamento precoce por conta própriaSimLGBTfobiaNãoNaNSimNa escola/universidade No shopping Espaços de lazerNão, nunca.NaNNãoNãoSim, inúmeras vezesSim, inúmeras vezesNãoNãoPrefiro não dizerNaNVerbalmente/ com xingamentosEra um homem brancoNãoNaNNaNNaNNaNNaNNaNNãoNãoNão, nunca aconteceuNão, nunca aconteceuNãoNãoNaNNão fui criada em nenhuma crença religiosaNada próximaNãoNãoNãoNãoNãoNãoCelular pré-pago (dados limitados + aplicativos)SimInstagram Facebook Whatsapp TelegramLazerRacismo LGBTfobia Machismo Intolerância religiosa Xingamentos e/ou humilhaçõesConta bloqueada/excluídaNunca preciseiNaNNaNNãoSimQuase nunca vouNunca fuiSim, mas não frequentoNão, não tenho esse costumeNada importanteNão, os ingressos para esses eventos são carosNaNNão tenho conhecimentoSim, e frequentoNão conheço nenhumNãoIndumentária (desenho e/ou confecção de roupas)NaN
9HeterossexualMulher transNãoNegra34.0RocinhaNãoNaNEnsino médio incompletoCertidão de Nascimento Carteira de Identidade (RG) CPF Carteira de Trabalho Título de EleitorNãoCertidão de Nascimento Carteira de Trabalho Título de EleitorRio de JaneiroNaNNãoNaNNãoMoro sozinhaNaNEu mesma contei14.0Me levaram para igreja/rezaram Ficaram preocupados com a violência Minha mãe me acolheu e meu pai nãoBoaSim, depende de meus cuidados, porém não financeirosSimSimSim, filha(s) adotadasCasa toda de tijolo e cimento (alvenaria)NaNÁgua encanada ligada ao sistema de fornecimento público de água Banheiro com ligação à rede de esgoto Caixa d’agua ou cisterna Energia elétrica da rede de abastecimento (irregular)Mora de favorGeladeira Fogão Televisão Celular RádioDurmo num cômodo sozinho em cama/colchão/outros sozinhoFornecimento de energia elétrica Água encanada Escola/creche pública Escola/creche privadaRua asfaltadaPraça pública Quadra de futebol Centro comunitário Espaço de eventos e lazer Bailes e fluxos (funk, forró, reggae, rap, rock etc)SimEstou desempregadoNão, mas trabalho longeServiços geraisSimAté 99 reaisSim, em partesNaNSimNaNSim, assédio moral Sim, assédio sexual Sim, assédio psicológicosim, mais de uma vez/ regularmentesim, mais de uma vez/ regularmenteNão sei como devo fazer para acessarSimsimNaNSimNão, parei/desisti por outros motivosPúblicaSim, oferece livros didáticosFora da comunidade onde vivoNaNNaNViolências sofridos no âmbito escolarSimViolência de gênero/identidade de gênero Pela minha orientação sexualSim, sofri/sofro algumas vezesPor parte dos alunosNaNNaNSim, apenas um(a) ou poucosNãoNãonãoSimSimSimNaNVou mais de duas vezes ao anoPelo menos uma ou duas vezes ao anoSimPositivoSimPositivoSimNegativoPrefiro não responderNaNSimPara aceleração metabólica (ganho muscular, uso dietário)NãoSimSimSimMaconha CocaínaNaNSim, e frequento(ei) por vontade própriaSimSimSim, e o serviço é bomSim, e já estou imunizadaNão sei/ não lembroNão possuoSim, mas não possuo laudoSim, uma vez ao diaSim, uma vezSim, regularmenteNaNNãoNaNSim, por amigos ou familiaresNãoNaNSim, mais de uma vezNa comunidade onde vivo Na escola/universidade No trabalho No ambiente familiarNãoNaNNão, nunca.NaNSim, uma vezNãoSim, inúmeras vezesSim, inúmeras vezesSim, inúmeras vezesNãoNão acredito que esse tipo de serviço funcione (credibilidade)Agente público de segurança (policial militar, civil, guarda municipal, polícia federal etc) Homem da minha comunidade Mulher da minha comunidade Homem na ruaVerbalmente/ com xingamentos Fisicamente, com tapas, chutes, soco e pontapésEra um homem negro/pardoCom frequênciaPOUCAS vezes fui abordada de acordo com minha identidade de gêneroSimSimSim, na zona sul do Rio de JaneiroPrefiro não responderSimSimSimSim, poucas vezesSim, várias vezesPrefiro não responderSimCatólicaCatólicaPraticanteSimSimSimSimSim, dentro da minha casa ou de parentesNão seiCelular pré-pago (dados limitados + aplicativos) Por pontos de wi-fi abertos pela cidade (internet provida por governo/empresas)SimInstagram Facebook WhatsappTrabalhoLGBTfobiaPost removido Conta bloqueada/excluídaSim, durante a pandemiaAuxílio emergencial / cadastro únicoDificuldade em acessar a internetNãoNãoQuase nunca vouQuase nunca vouSim, mas não frequentoSim, mas leio com pouca frequênciaImportanteSim, participo com frequência de eventos dentro e fora da favela onde vivoNem sempre, às vezes acontecem na favela onde vivoNão tenho conhecimentoNão sei responderSim, mas poucosSimDança (passinho, samba, etc) Música (cantor, produtor, instrumentista, etc) Teatro FotografiaNaN

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47BissexualHomem CisgêneroNãoBranca21.0Vila KennedyNãoNaNEnsino superior incompletoCertidão de Nascimento Carteira de Identidade (RG) CPF Carteira de Trabalho Título de EleitorSimNaNParaíbaNaNsem respostaNaNNãoMoro com duas pessoasFamíliaEu mesma contei15.0Me apoiaram/acolheramExcelenteNão, não sou responsável por ninguém em meu ambiente domiciliarNãoSimNão, mas quero terCasa toda de tijolo e cimento (alvenaria)NaNÁgua encanada ligada ao sistema de fornecimento público de água Banheiro com ligação à rede de esgoto Caixa d’agua ou cisterna Energia elétrica da rede de abastecimento (regularizada)Casa própriaComputador Geladeira Fogão Microondas Televisão Ar condicionado Máquina de lavar roupa Celular RádioDurmo num cômodo sozinho em cama/colchão/outros sozinhoFornecimento de energia elétrica Água encanada Sistema de esgoto Coleta de lixo Escola/creche pública Escola/creche privada Posto de atendimento médicoRua asfaltadaPraça pública Quadra de futebol Quadra poliesportiva Espaço cultural Centro comunitário Espaço de eventos e lazer Bailes e fluxos (funk, forró, reggae, rap, rock etc)NãoSou trabalhador informal (MEI, bico, freelancer)SimAtendente de loja/ fastfoodNãoDe 500 a 1.099 reaisSim, em partesNãoNãoIsso não é uma questão para mimNão, nunca sofri nenhum tipo de assédio no trabalhonão, nunca sofrinão, nunca sofriNão, porque não me enquadrei nos requisitosNãonãoNãoNão, porque não me enquadrei nos requisitosSimPúblicaSim, oferece livros didáticos Sim, oferece cadernos, lápis, canetas…Perto, na mesma comunidade em que vivoÔnibusTive mais tempo para me dedicar aos estudosNaNSimPela minha orientação sexualNunca sofri/sofroNão consigo definirNãoSimSim, apenas um(a) ou poucosSim, apenas um(a) ou poucosNãonãoSimNãoNãoNaNPelo menos uma ou duas vezes ao anoRaramente vouNãoNaNNãoNaNNãoNaNNãoNaNNãoNaNNaNNãoNãoNãoNunca utilizei nenhuma dessas substânciasNaNTenho a possibilidade de frequentar mas nunca fuiSimSimSim, e o serviço é bomSim, e já estou imunizadaNão sei/ não lembroNão possuoNão possuo nenhum diagnósticoSim, três ou mais vezes ao diaNaNSim, ocasionalmenteNaNNãoNaNNão Fiz tratamento precoce por conta própriaNãoNaNNãoNaNNãoNaNSim, na infânciaNa casa de parentesNãoNãoSim, uma vezSim, uma vezSim, inúmeras vezesNãoPrefiro não dizerNaNNaNNaNSim, antes dos meus 18 anos.SimSimNãoSim, na zona oeste do Rio de JaneiroNãoNaNSimSimSim, várias vezesSim, várias vezesNãoNãoNaNNão fui criada em nenhuma crença religiosaNada próximaNão seiNão seiNãoNãoNaNNão seiInternet celular pós-paga (franquia de dados + aplicativos) Tenho um plano residencial de internetSimInstagram Facebook Whatsapp Tiktok Twitter Tinder, grindr outros apps de paqueraTrabalho Estudo Lazer Grupos de apoio Conhecer gente nova Conectar com a família Acesso a serviçosNaNNaNSim, durante a pandemiaCarteira de trabalho digitalDificuldade em acessar a internetSimSimVou com frequênciaQuase nunca vouSim, mas não frequentoSim, leio com frequência a livros, revistas digitais e/ou artigos onlinePouco importanteNão, é caro me locomover até elesNaNA maioria dos eventos que acesso são promovidos por organizações civisSim, mas nunca fuiSim, conheço váriosNão seiMúsica (cantor, produtor, instrumentista, etc) Teatro Literatura/escritaNaN
48BissexualMulher CisgêneraNãoNegra22.0Vila KennedyNãoNaNEnsino superior incompletoCertidão de Nascimento Carteira de Identidade (RG) CPF Carteira de Trabalho Título de EleitorSimNaNRio de JaneiroNaNsem respostaNaNSimMoro com três pessoasFamíliaEu mesma contei20.0Me apoiaram/acolheramBoaNão, não sou responsável por ninguém em meu ambiente domiciliarNãoSimNão, mas quero terCasa toda de tijolo e cimento (alvenaria)NaNÁgua encanada ligada ao sistema de fornecimento público de água Banheiro com ligação à rede de esgoto Caixa d’agua ou cisterna Energia elétrica da rede de abastecimento (regularizada)Casa própriaComputador Geladeira Fogão Televisão Ar condicionado CelularDurmo num cômodo sozinho em cama/colchão/outros sozinhoFornecimento de energia elétrica Água encanada Sistema de esgoto Coleta de lixo Escola/creche pública Escola/creche privada Posto de atendimento médicoRua asfaltadaPraça pública Espaço cultural Parque arborizado Espaço de eventos e lazer Bailes e fluxos (funk, forró, reggae, rap, rock etc)NãoEstou desempregadoNaNNaNNãoDe 500 a 1.099 reaisSim, em partesNaNNaNNaNNaNNaNNaNSimNaNNaNNaNSimSimPúblicaSim, oferece livros didáticos Sim, oferece cadernos, lápis, canetas… Sim, oferece uniformeFora da comunidade onde vivoÔnibusNão consegui me adaptar ao novo modelo de ensinoNaNSimViolência de gênero/identidade de gênero Racismo Pela minha orientação sexualNunca sofri/sofroNaNNaNSimSim, apenas um(a) ou poucosSim, apenas um(a) ou poucosSim, apenas um(a) ou poucosNão sei o que éNãoNãoNãoNãoPelo menos uma ou duas vezes ao anoPelo menos uma ou duas vezes ao anoNãoNaNNãoNaNNãoNaNNãoNaNNãoNaNNaNNãoNãoSimMaconhaNaNNãoNãoNão seiSim, e o serviço é bomSim, e já estou imunizadaHepatite B e C Gripe Sarampo Poliomielite Febre Amarela Tríplice Viral BCG-Turberculose Dupla-TétanoNão possuoNão possuo nenhum diagnósticoSim, três ou mais vezes ao diaNaNSim, ocasionalmenteNaNSimLeve, com pouco sintomasNãoSimAgressão verbal/física Violência psicológicaNãoNaNNãoNaNSim, na infânciaNa casa de vizinhos Em festasNãoNãoSim, uma vezSim, uma vezSim, uma vezNãoNão conheço tais centros.Homem da minha comunidade Mulher da minha comunidade Um familiarVerbalmente/ com xingamentosEra um homem branco Era uma mulher branca Era uma mulher negra/pardaNãoNaNNaNNaNNaNNaNNaNNãoSimSim, com frequênciaSim, com frequênciaNãoNãoNaNNão fui criada em nenhuma crença religiosaPouco próximaSimNãoNãoNãoNãoSimInternet celular pós-paga (franquia de dados + aplicativos) Tenho um plano residencial de internetSimInstagram Whatsapp Twitter TelegramEstudo Ativismo Lazer Se informarNunca sofri nenhuma dessas situaçõesNaNSim, antes e durante a pandemiaNaNNaNSimDepende da situaçãoVou com frequênciaVou com frequênciaNãoSim, leio com frequência a livros, revistas digitais e/ou artigos onlineExtremamente importanteSim, participo com frequência de eventos dentro e fora da favela onde vivoSim, sempre acontecem longe de onde vivoSim, aconteceu poucas vezesSim, e frequentoNão conheço nenhumSimDança (passinho, samba, etc) Artes visuais (pintura, escultura, etc) FotografiaNaN
49Lésbica/ SapatãoMulher CisgêneraNãoNegra24.0Favela da Carobinha, Campo Grande (ZO-RJ)NãoNaNEnsino superior incompletoCertidão de Nascimento Carteira de Identidade (RG) CPF Carteira de Trabalho Título de EleitorNãoCarteira de TrabalhoRio de JaneiroNaNsem respostaNaNSimMoro com três pessoasFamíliaDe outras maneiras17.0Meu pai me acolheu e minha mãe nãoBoaNão, não sou responsável por ninguém em meu ambiente domiciliarNão sei especificarNãoNão e, não pretendo terCasa toda de tijolo e cimento (alvenaria)NaNÁgua encanada ligada ao sistema de fornecimento público de água Banheiro com ligação à rede de esgoto Caixa d’agua ou cisterna Energia elétrica da rede de abastecimento (irregular)Casa própriaComputador Geladeira Fogão Televisão Máquina de lavar roupa Celular RádioDurmo num cômodo sozinho em cama/colchão/outros sozinhoÁgua encanada Coleta de lixo Escola/creche pública Posto de atendimento médicoTerra/chão batidoPraça pública Bailes e fluxos (funk, forró, reggae, rap, rock etc)NãoEstou desempregadoNão, mas trabalho pertotrabalho informal, venda de roupasPrefiro não responderAté 99 reaisSim, completamenteNãoNãoIsso não é uma questão para mimNão, nunca sofri nenhum tipo de assédio no trabalhonão, nunca sofrinão, nunca sofriNão soliciteiNãonão seiNãoNão, porque fui recusadaSimPúblicaNão oferece materiais gratuitosFora da comunidade onde vivoÔnibus Metrô A péTive mais tempo para me dedicar aos estudosNaNSimViolência de gênero/identidade de gênero Racismo Pela minha orientação sexual Pelo meu comportamento (psicofobia, transtornos, etc.)Nunca sofri/sofroNaNSimSimSim, apenas um(a) ou poucosSim, apenas um(a) ou poucosSim, apenas um(a) ou poucosnãoSimSimNãoNãoPelo menos uma ou duas vezes ao anoPelo menos uma ou duas vezes ao anoNãoNaNNãoNaNNãoNaNNãoNaNNãoNaNNaNNãoSimNãoMaconha LSDO serviço é limitadoSim, e frequento(ei) por vontade própriaNãoSimNãoSim, e já estou imunizadaHepatite B e C Gripe Sarampo Poliomielite Febre Amarela BCG-Turberculose Não sei/ não lembroNão possuoSim, com laudo psiquiátricoSim, três ou mais vezes ao diaNão seiSim, ocasionalmenteNaNNãoNaNSim, por amigos ou familiaresSimViolência ginecológica LGBTfobiaNãoNaNNãoNaNNão, nunca.NaNNãoNãoSim, inúmeras vezesSim, inúmeras vezesSim, inúmeras vezesNãoPrefiro não dizerAgente público da saúde (médico/a, enfermeiro/a, técnico/a em enfermagem, maqueiro, etc) Homem na rua Mulher na ruaVerbalmente/ com xingamentosEra um homem brancoSim, antes e depois dos meus 18 anos.SimSimNãoSim, na zona sul do Rio de JaneiroSimNãoSimNãoSim, várias vezesSim, várias vezesNãoNãoNaNNão fui criada em nenhuma crença religiosaNada próximaNão seiNãoNãoNãoNãoSimCelular pré-pago (dados limitados + aplicativos) Tenho um plano residencial de internetSimInstagram Whatsapp Twitter Tinder, grindr outros apps de paqueraTrabalho Estudo Ativismo Lazer Grupos de apoio Se informar Conhecer gente nova Conectar com a família Flertes/relacionamentoRacismo LGBTfobia Preconceito de classe socialNunca tive esse tipo de problemasNão tenho certezaNaNNaNSimDepende da situaçãoQuase nunca vouQuase nunca vouNãoSim, mas leio com pouca frequênciaPouco importanteSim, participo com frequência de eventos dentro e fora da favela onde vivoSim, sempre acontecem longe de onde vivoNão, nunca aconteceuNão, acredito que não existaNão conheço nenhumNãoDança (passinho, samba, etc) Fotografia Literatura/escritaNaN
50BissexualHomem CisgêneroNãoBranca30.0MaréNãoNaNPós-graduação incompletaCertidão de Nascimento Carteira de Identidade (RG) CPF Carteira de Trabalho Título de EleitorSimNaNRio de JaneiroNaNsem respostaNaNNãoMoro com uma pessoaFamíliaSouberam por terceiros18.0Me agrediram Me xingaram Disseram que era apenas uma fase Meus pais não me acolheram mas outras pessoas da família simRuimSim depende financeiramente e de cuidadosSimNãoSim, filha(s) biológicasCasa toda de tijolo e cimento (alvenaria)NaNÁgua encanada ligada ao sistema de fornecimento público de água Caixa d’agua ou cisterna Banheiro sem ligação à rede de esgoto Energia elétrica da rede de abastecimento (irregular)Mora de favorComputador Geladeira Fogão Televisão Máquina de lavar roupa CelularDurmo num cômodo com mais pessoas e divido cama/colchão/outrosFornecimento de energia elétrica Água encanada Escola/creche pública Posto de atendimento médicoRua asfaltadaQuadra poliesportiva Parque infantil Bailes e fluxos (funk, forró, reggae, rap, rock etc)SimEstou empregadoNão, mas trabalho longeFuncionário públicoNãoDe 1.100 a 2.119 reaisSim, em partesNãoNãoIsso não é uma questão para mimNão, nunca sofri nenhum tipo de assédio no trabalhonão, nunca sofrinão, nunca sofriSimNãonão seiNãoNão, porque não me enquadrei nos requisitosSimPúblicaNão oferece materiais gratuitosFora da comunidade onde vivoÔnibusTive mais tempo para me dedicar aos estudosNaNSimPor ter uma deficiência física e/ou intelectual Pela minha orientação sexual Pelo meu comportamento (psicofobia, transtornos, etc.)Sim, sofri/sofro várias vezesPor parte dos alunos Por parte dos professores Por parte do corpo administrativoNãoNão seiNãoNãoNãonãoSimSimNãoNaNVou mais de duas vezes ao anoVou mais de duas vezes ao anoSimNegativoSimNegativoSimNegativoSimNegativoNãoNaNNaNNãoSimSimMaconha Cocaína Crack LSD OutrasNaNSim, e frequento(ei) por vontade própriaNão seiNão seiSim, mas o serviço é ruim, quase nunca tem medicamentosSim, e já estou imunizadaHepatite B e C Gripe Sarampo Poliomielite Febre Amarela Tríplice Viral BCG-Turberculose Pneumocócica Dupla-Tétano Triplice Bacteriana-dTpaSim, sou dependente do plano de saúde de outra pessoaSim, com laudo psiquiátricoSim, pelo menos duas vezes ao diaNão seiSim, ocasionalmenteNaNSimAssintomáticoSim, por outros/terceirosSimLGBTfobia Violência psicológica Psicofobia Assédio religiosoNãoNaNNãoNaNNão, nunca.NaNNãoNãoSim, inúmeras vezesSim, inúmeras vezesSim, inúmeras vezesNãoNão acredito que esse tipo de serviço funcione (credibilidade)Homem da minha comunidade Mulher da minha comunidade Um familiar Homem na rua Sofri uma agressão virtual por desconhecido/ perfil fakeVerbalmente/ com xingamentos Fisicamente, com tapas, chutes, soco e pontapés VirtualmenteEra um homem branco Era uma mulher branca Era um homem negro/pardo Era uma pessoa LGBTI brancaSim, antes e depois dos meus 18 anos.NãoSimNãoCuritiba, DouradosSimNãoNãoNãoSim, poucas vezesSim, poucas vezesNãoNãoNaNCatólicoNada próximaSimSimNãoSimNãoSimCelular pré-pago (dados limitados + aplicativos) Centros públicos (espaços culturais, telecentros etc) Por pontos de wi-fi abertos pela cidade (internet provida por governo/empresas)SimInstagram Whatsapp Twitter Tinder, grindr outros apps de paqueraTrabalho Estudo Ativismo Lazer Grupos de apoio Se informar Conhecer gente nova Conectar com a família Fazer compras Acesso a serviços Flertes/relacionamentoLGBTfobia Preconceito de classe social Machismo Intolerância religiosa Xingamentos e/ou humilhações Vazaram meus nudes Ameaças psicológicas e/ou de violência física Expuseram minha orientação sexual e identidade de gênero sem meu consentimentoConta invadida (ex. alguém entrou no meu perfil fingindo que era eu) Tive meus dados ou informações pessoais divulgadas (ex. usaram meu cpf para fraudes)Sim, durante a pandemiaCarteira de trabalho digital Auxílio emergencial / cadastro único Bolsa família Estudos durante a pandemia Documentos (título de eleitor, cpf, rg) Certificados diversos (antecedentes criminais, cadastro positivo etc) Acesso a serviços essenciais (luz, água, saneamento etc)Dificuldade em acessar a internet Dificuldade em encontrar informações corretas nos sites e em buscas Site/app indisponível Site/app muito complicado de usar Plano de dados não permite acessar esses serviçosSimNãoVou com frequênciaVou com frequênciaSim, mas não frequentoQuase nunca paro para lerExtremamente importanteSim, participo com frequência de eventos dentro e fora da favela onde vivoSim, sempre acontecem longe de onde vivoA maioria dos eventos que acesso são promovidos por organizações civisNão, acredito que não existaSim, mas poucosNão seiDança (passinho, samba, etc) Artes visuais (pintura, escultura, etc)NaN
51Gay/ BichaHomem CisgêneroNãoNegra48.0MaréNãoNaNEnsino médio completoCertidão de Nascimento Carteira de Identidade (RG) CPF Carteira de Trabalho Título de EleitorSimNaNRio de JaneiroNaNsem respostaNaNNãoMoro com três pessoasFamíliaEu mesma contei31.0Me apoiaram/acolheramBoaSim, depende de meus cuidados, porém não financeirosNãoSimNão, mas quero terCasa toda de tijolo e cimento (alvenaria)NaNÁgua encanada ligada ao sistema de fornecimento público de água Banheiro com ligação à rede de esgoto Caixa d’agua ou cisterna Energia elétrica da rede de abastecimento (regularizada) Energia elétrica da rede de abastecimento (irregular)Casa própriaComputador Geladeira Fogão Microondas Televisão Ar condicionado Celular RádioDurmo num cômodo com mais pessoas, porém em uma cama/colchão/outros só minhaFornecimento de energia elétrica Coleta de lixo Escola/creche pública Escola/creche privada Posto de atendimento médicoRua asfaltadaPraça pública Quadra de futebol Espaço cultural Centro comunitário Espaço de eventos e lazer Bailes e fluxos (funk, forró, reggae, rap, rock etc)SimEstou empregadoNão, mas trabalho longeFuncionário públicoNãoDe 1.100 a 2.119 reaisNãoNãoSimNaNSim, assédio moral Sim, assédio sexualsim, uma veznão, nunca sofriSimNãonãoNãoNão, porque não me enquadrei nos requisitosNão, parei/desisti por outros motivosPúblicaSim, oferece livros didáticosPerto, na mesma comunidade em que vivoNaNNaNFalta de tempo para estudar (tive que desistir de estudar para trabalhar, ou cuidar de alguém)NãoNaNNunca sofri/sofroNão consigo definirNaNNaNSim, apenas um(a) ou poucosSim, apenas um(a) ou poucosNãonãoSimNãoNãoNaNVou mais de duas vezes ao anoPelo menos uma ou duas vezes ao anoSimNegativoSimPositivoNãoNaNNãoNaNNãoNaNNaNNãoNãoSimNunca utilizei nenhuma dessas substânciasNaNSim, e frequento(ei) por vontade própriaNão seiNão seiSim, mas o serviço é ruim, quase nunca tem medicamentosSim, e já estou imunizadaGripe Sarampo Febre Amarela Tríplice Viral BCG-Turberculose Dupla-TétanoNão possuoNão possuo nenhum diagnósticoSim, três ou mais vezes ao diaNão seiSim, ocasionalmenteNaNNãoNaNSim, por amigos ou familiaresNãoNaNSim, uma vezEspaços públicosNãoNaNNão, nunca.NaNNãoSimNãoSim, uma vezSim, inúmeras vezesSimNaNHomem na rua Funcionário/a de empresa/lojaVerbalmente/ com xingamentos Fisicamente, com uma faca ou objeto cortanteEra um homem negro/pardoSim, depois dos meus 18 anos.SimNãoSimSim, na zona norte do Rio de JaneiroNãoSimNãoNãoSim, várias vezesSim, poucas vezesNãoSimCatólicoCatolicismoPraticanteNãoNãoNãoNãoNãoNãoInternet celular pós-paga (franquia de dados + aplicativos)SimFacebook Whatsapp Tinder, grindr outros apps de paqueraLazer Conhecer gente nova Conectar com a famíliaPreconceito de classe socialPost removidoSim, antes e durante a pandemiaNaNNaNSimDepende da situaçãoQuase nunca vouQuase nunca vouSim, mas não frequentoSim, leio com frequência a livros, revistas digitais e/ou artigos onlineExtremamente importanteSim, participo com frequência de eventos dentro e fora da favela onde vivoSim, sempre acontecem longe de onde vivoA maioria dos eventos que acesso são promovidos por organizações civisNão sei responderNão conheço nenhumSimDança (passinho, samba, etc) Indumentária (desenho e/ou confecção de roupas) Música (cantor, produtor, instrumentista, etc) Literatura/escritaNaN
52HeterossexualTravestiNãoNegra32.0MaréNãoNaNEnsino fundamental incompletoCertidão de Nascimento Carteira de Identidade (RG) CPF Carteira de Trabalho Título de EleitorSimNaNRio de JaneiroNaNSimSimSimMoro com mais que cinco pessoasFamíliaSouberam por terceiros10.0Disseram que era apenas uma fase Minha mãe me acolheu e meu pai nãoIndiferenteNão, não sou responsável por ninguém em meu ambiente domiciliarNãoSimNão e, não pretendo terCasa toda de tijolo e cimento (alvenaria)NaNÁgua encanada ligada ao sistema de fornecimento público de água Banheiro com ligação à rede de esgoto Caixa d’agua ou cisterna Energia elétrica da rede de abastecimento (irregular)Casa própriaComputador Geladeira Fogão Televisão Ar condicionado Máquina de lavar roupa Celular Forninho ElétricoDurmo num cômodo com mais pessoas, porém em uma cama/colchão/outros só minhaFornecimento de energia elétrica Água encanada Sistema de esgoto Escola/creche pública Escola/creche privada Posto de atendimento médicoRua asfaltadaPraça pública Quadra de futebol Espaço cultural Centro comunitário Bailes e fluxos (funk, forró, reggae, rap, rock etc)NãoEstou desempregadoNão, mas trabalho pertoProfissional do sexoSimDe 1.100 a 2.119 reaisSim, em partesNãoSimNaNSim, assédio moral Sim, assédio sexual Sim, assédio psicológicosim, mais de uma vez/ regularmentenão, nunca sofriSimNãonãoNãoNão, porque não me enquadrei nos requisitosNão, parei/desisti por vontade própriaPúblicaSim, oferece livros didáticos Sim, oferece cadernos, lápis, canetas… Sim, oferece uniformePerto, na mesma comunidade em que vivoNaNNaNNaNNãoNaNNunca sofri/sofroNão consigo definirNaNNaNSim, apenas um(a) ou poucosNãoNãonãoSimSimSimNaNVou mais de duas vezes ao anoNunca vouSimPositivoSimPositivoSimNegativoSimNegativoSimPara terapia hormonal (mudanças corporais)NãoSimSimNãoMaconha Cocaína LSD EstaseO serviço é limitadoNãoNão seiSimSim, mas o serviço é ruim, quase nunca tem medicamentosSim, e já estou imunizadaHepatite B e C Gripe Sarampo Poliomielite Febre Amarela Tríplice Viral BCG-Turberculose HPV Pneumocócica Dupla-Tétano Triplice Bacteriana-dTpaNão possuoNão possuo nenhum diagnósticoSim, pelo menos duas vezes ao diaSim, uma vezNão utilizoOs serviços são ruinsNãoNaNNãoNãoNaNSim, mais de uma vezNa comunidade onde vivo Espaços públicosSimCasa de ShowSim, na adolescênciaNa ruaSim, uma vezNãoSim, inúmeras vezesSim, inúmeras vezesNãoNãoNão acredito que esse tipo de serviço funcione (credibilidade)Agente público de segurança (policial militar, civil, guarda municipal, polícia federal etc) Homem da minha comunidade Mulher da minha comunidade Homem na rua Mulher na rua Sofri uma agressão virtual por desconhecido/ perfil fakeVerbalmente/ com xingamentos Fisicamente, com tapas, chutes, soco e pontapés Fisicamente, com uma madeira ou objeto Fisicamente, sexualmente Fisicamente, com uma faca ou objeto cortante Fisicamente, com uma arma de fogo VirtualmenteEra um homem branco Era uma mulher branca Era um homem negro/pardo Era uma mulher negra/parda Era uma pessoa LGBTI negra Era uma pessoa LGBTI brancaSim, antes e depois dos meus 18 anos.NãoSimSimSim, na zona norte do Rio de JaneiroSimSimSimSimNão, nunca aconteceuNão, nunca aconteceuNãoSimVou pra igreja, pra Macumba... em tudo.EvangélicaPouco próximaNãoNãoNãoSimNãoNãoCentros públicos (espaços culturais, telecentros etc) Internet por redes de vizinhos Internet celular pós-paga (franquia de dados + aplicativos) Tenho um plano residencial de internetSimInstagram Facebook WhatsappTrabalho Lazer Conhecer gente nova Conectar com a família Fazer compras Acesso a serviçosRacismo LGBTfobia Preconceito de classe social Machismo Intolerância religiosa Xingamentos e/ou humilhações Vazaram meus nudes Ameaças psicológicas e/ou de violência física Expuseram minha orientação sexual e identidade de gênero sem meu consentimento Assédio sexual Linchamento virtual CancelamentoPost removido Conta bloqueada/excluída Palavras censuradas (ex. nao consigo postar a palavra “sapatao” no insta) Conta invadida (ex. alguém entrou no meu perfil fingindo que era eu) Conta roubada (ex. nao consegui mais ter acesso) Tive problemas com verificação de identidade (ex. pediram meu documento e ele nao bate com meu nome social) Dados de telefone vazadosSim, antes e durante a pandemiaNaNNaNSimDepende da situaçãoQuase nunca vouQuase nunca vouSim, mas não frequentoNão, não tenho esse costumeNada importanteNão, é caro me locomover até elesNaNNão tenho conhecimentoSim, mas nunca fuiNão conheço nenhumSimNão tenho interesseNaN
53HeterossexualTravestiNãoNegra38.0MaréNãoNaNEnsino médio completoCertidão de Nascimento Carteira de Identidade (RG) CPF Carteira de Trabalho Título de EleitorSimNaNRio de JaneiroNaNSimSimSimMoro com duas pessoasFamíliaSouberam por terceiros13.0Meus pais não me acolheram mas outras pessoas da família simExcelenteSim, depende de mim financeiramenteSimSimNão e, não pretendo terCasa toda de tijolo e cimento (alvenaria)NaNÁgua encanada ligada ao sistema de fornecimento público de água Banheiro com ligação à rede de esgoto Caixa d’agua ou cisterna Energia elétrica da rede de abastecimento (regularizada) Energia elétrica da rede de abastecimento (irregular)Casa própriaComputador TV a Cabo Geladeira Fogão Microondas Televisão Ar condicionado Máquina de lavar roupa CelularDurmo num cômodo sozinho em cama/colchão/outros sozinhoFornecimento de energia elétrica Água encanada Sistema de esgoto Coleta de lixo Escola/creche pública Escola/creche privada Posto de atendimento médicoRua asfaltadaPraça pública Quadra de futebol Quadra poliesportiva Espaço cultural Parque arborizado Centro comunitário Espaço de eventos e lazer Bailes e fluxos (funk, forró, reggae, rap, rock etc)NãoSou trabalhador informal (MEI, bico, freelancer)SimSociedade CivilSimDe 1.100 a 2.119 reaisNãoSimSimNaNSim, assédio sexual Sim, assédio psicológicosim, mais de uma vez/ regularmentenão, nunca sofriSimNãonãoNãoNão, porque não me enquadrei nos requisitosNão, já concluí meus estudosPúblicaSim, oferece livros didáticosPerto, na mesma comunidade em que vivoNaNNaNNaNSimViolência de gênero/identidade de gênero Pela minha orientação sexualSim, sofri/sofro várias vezesPor parte dos alunosNaNNaNSim, vários(as)Sim, apenas um(a) ou poucosNãosim, já utilizeiSimSimNãoNaNVou mais de duas vezes ao anoRaramente vouSimNegativoSimPositivoSimNegativoSimNegativoJá utilizei no passado, agora não uso maisNaNNaNSimSó às vezes, raramente.NãoMaconha CocaínaO serviço é limitadoSim, e frequento(ei) por vontade própriaNão seiSimNão seiSim, e já estou imunizadaHepatite B e C Gripe Sarampo Poliomielite Tríplice Viral BCG-Turberculose HPV Pneumocócica Dupla-Tétano Triplice Bacteriana-dTpaNão possuoSim, com laudo psiquiátricoSim, três ou mais vezes ao diaNão seiNão utilizoOs serviços são ruinsSimLeve, com pouco sintomasNão Fiz tratamento precoce por conta própriaSimLGBTfobiaSim, mais de uma vezNa comunidade onde vivo Na escola/universidade No ambiente familiar Espaços públicos Transporte (táxi, uber, ônibus, metrô, trem etc.) Fora da comunidade tambémSimRestaurante PopularSim, na infância Sim, na adolescência Sim, na vida adultaNa rua Em festasSim, uma vezSimSim, inúmeras vezesSim, inúmeras vezesSim, inúmeras vezesSimNaNAgente público de segurança (policial militar, civil, guarda municipal, polícia federal etc) Agente público da saúde (médico/a, enfermeiro/a, técnico/a em enfermagem, maqueiro, etc) Homem da minha comunidade Mulher da minha comunidade Um familiar Homem na rua Sofri uma agressão virtual por desconhecido/ perfil fakeVerbalmente/ com xingamentos Fisicamente, com tapas, chutes, soco e pontapés Fisicamente, com uma madeira ou objeto Fisicamente, sexualmente Fisicamente, com uma faca ou objeto cortante Fisicamente, com uma arma de fogo VirtualmenteEra um homem branco Era uma mulher branca Era um homem negro/pardo Era uma mulher negra/parda Era uma pessoa LGBTI negra Era uma pessoa LGBTI brancaSim, antes e depois dos meus 18 anos.SimSimSimSim, na zona norte do Rio de JaneiroSimSimSimSimSim, várias vezesSim, várias vezesSimSimCandombléUmbandaPraticanteSimSimNãoSimNãoSimCelular pré-pago (dados limitados + aplicativos) Internet do trabalho / escola / universidade Internet por redes de vizinhos Por pontos de wi-fi abertos pela cidade (internet provida por governo/empresas)SimFacebook Whatsapp Tiktok Tinder, grindr outros apps de paquera BadooTrabalho Lazer Se informar Conhecer gente nova Conectar com a família Acesso a serviços Flertes/relacionamentoRacismo LGBTfobia Preconceito de classe social Machismo Intolerância religiosa Xingamentos e/ou humilhações Ameaças psicológicas e/ou de violência física Expuseram minha orientação sexual e identidade de gênero sem meu consentimento Assédio sexualConta bloqueada/excluída Palavras censuradas (ex. nao consigo postar a palavra “sapatao” no insta) Dados de telefone vazadosSim, antes e durante a pandemiaNaNNaNSimDepende da situaçãoVou com frequênciaQuase nunca vouSim, mas não frequentoQuase nunca paro para lerMuito importanteSim, participo com frequência de eventos dentro e fora da favela onde vivoNem sempre, às vezes acontecem na favela onde vivoA maioria dos eventos que acesso são promovidos por organizações civisSim, e frequentoSim, mas poucosSimArtes visuais (pintura, escultura, etc) Indumentária (desenho e/ou confecção de roupas)NaN
54BissexualMulher CisgêneraNãoBranca23.0Ceilândia - DFNãoNaNEnsino superior completoCertidão de Nascimento Carteira de Identidade (RG) CPF Título de EleitorSimNaNDistrito FederalNaNsem respostaNaNSimMoro com mais que cinco pessoasFamíliaDe outras maneiras23.0Me xingaram Me levaram para igreja/rezaramRuimSim depende financeiramente e de cuidadosNão sei especificarNãoSim, filha(s) biológicasCasa toda de tijolo e cimento (alvenaria)NaNÁgua encanada ligada ao sistema de fornecimento público de água Banheiro com ligação à rede de esgoto Caixa d’agua ou cisterna Energia elétrica da rede de abastecimento (irregular)Casa própriaGeladeira Fogão Microondas Televisão Máquina de lavar roupa CelularDurmo num cômodo com mais pessoas, porém em uma cama/colchão/outros só minhaFornecimento de energia elétrica Água encanada Sistema de esgoto Coleta de lixo Escola/creche pública Escola/creche privada Posto de atendimento médicoRua e terraPraça pública Quadra de futebol Parque infantilNãoEstou desempregadoNão, mas trabalho longeÁrea da educaçãoNãoAté 99 reaisSim, completamenteNãoNãoIsso não é uma questão para mimSim, assédio moralnão, nunca sofrinão, nunca sofriNão soliciteiSimnãoSimSimSimPúblicaSim, oferece livros didáticosFora da comunidade onde vivoÔnibus MetrôNão consegui me adaptar ao novo modelo de ensinoNaNNãoNaNNunca sofri/sofroNão consigo definirSimSimSim, apenas um(a) ou poucosSim, váriosSim, apenas um(a) ou poucosNão sei o que éNãoSimNãoSimPelo menos uma ou duas vezes ao anoRaramente vouSimNegativoSimNegativoSimNegativoSimNegativoNãoNaNNaNNãoSimSimMaconhaNaNSim, e frequento(ei) por vontade própriaSimSimSim, mas o serviço é ruim, quase nunca tem medicamentosSim, e já estou imunizadaHepatite B e C Gripe Sarampo Poliomielite Febre Amarela Tríplice Viral BCG-Turberculose HPV Triplice Bacteriana-dTpaSim, sou dependente do plano de saúde de outra pessoaSim, com laudo psiquiátricoSim, três ou mais vezes ao diaNão seiNão utilizoNão consegui realizar meu cadastroNãoNaNSim, por amigos ou familiares Sim, por médicos particularesSimViolência obstétrica Violência ginecológicaNãoNaNNãoNaNNão, nunca.NaNNãoNãoSim, uma vezSim, uma vezNão tenho certeza/Não percebiNãoPrefiro não dizerUm familiarVerbalmente/ com xingamentosEra um homem branco Era uma mulher brancaSim, depois dos meus 18 anos.SimNãoSimDFSimSimNãoNãoNão, nunca aconteceuNão, nunca aconteceuNãoSimCatólica/espíritaCatólicaPouco próximaSimNão seiNãoSimSim, dentro da minha casa ou de parentesNão seiSó tenho acesso ao whatsapp no celular, porque é gratuito Internet do trabalho / escola / universidade Por pontos de wi-fi abertos pela cidade (internet provida por governo/empresas) Tenho um plano residencial de internetSimInstagram Facebook Whatsapp Twitter TelegramTrabalho Estudo Se informarNunca sofri nenhuma dessas situaçõesPalavras censuradas (ex. nao consigo postar a palavra “sapatao” no insta)Sim, durante a pandemiaAuxílio emergencial / cadastro único Estudos durante a pandemia Documentos (título de eleitor, cpf, rg) Certificados diversos (antecedentes criminais, cadastro positivo etc)Plano de dados não permite acessar esses serviçosSimDepende da situaçãoVou com frequênciaQuase nunca vouSim, mas não frequentoSim, leio com frequência a livros, revistas digitais e/ou artigos onlineImportanteSim, participo com frequência de eventos dentro e fora da favela onde vivoNem sempre, às vezes acontecem na favela onde vivoSim, aconteceu poucas vezesSim, mas nunca fuiNão conheço nenhumNão seiArtes visuais (pintura, escultura, etc) Indumentária (desenho e/ou confecção de roupas) Fotografia Literatura/escritaNaN
55Lésbica/ SapatãoMulher CisgêneraNãoBranca28.0Não moro em comunidadeNãoNaNPós-graduação completaCertidão de Nascimento Carteira de Identidade (RG) CPF Título de EleitorSimNaNRio de JaneiroNaNsem respostaNaNNãoNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNSim, depois dos meus 18 anos.SimNãoNãoSim, fora da cidade do Rio de JaneiroNãoNãoNãoNãoNão, nunca aconteceuNão, nunca aconteceuNãoNãoNaNCatolicismoNada próximaSimNãoNãoNãoNãoNão seiInternet celular pós-paga (franquia de dados + aplicativos) Tenho um plano residencial de internetSimWhatsappTrabalho Estudo Ativismo LazerLGBTfobiaNunca tive esse tipo de problemasNão tenho certezaNaNNaNNãoDepende da situaçãoQuase nunca vouQuase nunca vouNãoSim, leio com frequência a livros, revistas digitais e/ou artigos onlineImportanteNão, é caro me locomover até elesNaNNão tenho conhecimentoNão, acredito que não existaNão conheço nenhumNão seiMúsica (cantor, produtor, instrumentista, etc) Fotografia Literatura/escritaNaN
56HeterossexualMulher transNãoNegra36.0FazendinhaNãoNaNEnsino superior completoCertidão de Nascimento Carteira de Identidade (RG) CPF Carteira de Trabalho Título de EleitorSimNaNRio de JaneiroNaNSimSimNãoMoro sozinhaNaNEu mesma contei16.0Me xingaram Ficaram preocupados com a violência Meus pais não me acolheram mas outras pessoas da família simBoaNão, não sou responsável por ninguém em meu ambiente domiciliarSimNãoNão, mas quero terCasa toda de tijolo e cimento (alvenaria)NaNÁgua encanada ligada ao sistema de fornecimento público de água Banheiro com ligação à rede de esgoto Caixa d’agua ou cisterna Energia elétrica da rede de abastecimento (irregular)Paga aluguelComputador Geladeira Fogão Microondas Televisão Ar condicionado Máquina de lavar roupa CelularDurmo num cômodo sozinho em cama/colchão/outros sozinhoFornecimento de energia elétrica Água encanadaRua asfaltadaQuadra de futebol Centro comunitário Bailes e fluxos (funk, forró, reggae, rap, rock etc)NãoSou trabalhador informal (MEI, bico, freelancer)Não, mas trabalho longeAssistente pessoalSimDe 1.100 a 2.119 reaisNãoSimSimNaNSim, assédio moral Sim, assédio psicológicosim, mais de uma vez/ regularmentenão, nunca sofriNão, porque não me enquadrei nos requisitosNãosimNãoNão, porque não me enquadrei nos requisitosSimPúblicaSim, oferece cadernos, lápis, canetas…Fora da comunidade onde vivoA péNão consegui me adaptar ao novo modelo de ensinoNaNSimViolência de gênero/identidade de gênero RacismoSim, sofri/sofro poucas vezesPor parte dos alunosSimNão seiNãoSim, váriosNãonãoSimSimSimNaNPelo menos uma ou duas vezes ao anoPelo menos uma ou duas vezes ao anoSimPositivoSimPositivoSimPositivoSimNegativoSimPara terapia hormonal (mudanças corporais)NãoNãoNãoNãoNunca utilizei nenhuma dessas substânciasPrefiro me consultar em outros lugaresSim, e frequento(ei) por vontade própriaNão seiNão seiNão seiSim, e já estou imunizadaGripe Sarampo Poliomielite Febre Amarela Tríplice Viral BCG-Turberculose Pneumocócica Dupla-Tétano Triplice Bacteriana-dTpaNão possuoSim, mas não possuo laudoSim, pelo menos duas vezes ao diaNão seiSim, ocasionalmenteNaNSimLeve, com pouco sintomasSim, por amigos ou familiares Sim, por outros/terceirosSimLGBTfobia Violência psicológicaSim, mais de uma vezNa comunidade onde vivo Na escola/universidade No trabalho No ambiente familiar Espaços públicos Transporte (táxi, uber, ônibus, metrô, trem etc.)SimNa escola/universidade No trabalho Numa boateSim, na infância Sim, na adolescênciaNa rua OutrosSim, mais de uma vezSimSim, inúmeras vezesSim, inúmeras vezesSim, inúmeras vezesSimNaNAgente público de segurança (policial militar, civil, guarda municipal, polícia federal etc) Agente público da saúde (médico/a, enfermeiro/a, técnico/a em enfermagem, maqueiro, etc) Agente público da educação (professor/a, diretor/a, coordenador pedagógico, etc) Homem da minha comunidade Mulher da minha comunidade Um familiar Homem na rua Mulher na rua Funcionário/a de empresa/loja Sofri uma agressão virtual por desconhecido/ perfil fakeVerbalmente/ com xingamentos Fisicamente, com tapas, chutes, soco e pontapés Fisicamente, sexualmente Fisicamente, com uma arma de fogo VirtualmenteEra um homem branco Era uma mulher branca Era um homem negro/pardoSim, antes e depois dos meus 18 anos.NãoSimSimSim, na zona norte do Rio de Janeiro Sim, na zona oeste do Rio de JaneiroSimSimSimSimSim, com frequênciaSim, poucas vezesSimSimUmbandaEvangélicaPraticanteSimSimSimSimSim, dentro da minha casa ou de parentesNão seiInternet do trabalho / escola / universidade Por pontos de wi-fi abertos pela cidade (internet provida por governo/empresas) Tenho um plano residencial de internetSimInstagram Facebook Whatsapp Tinder, grindr outros apps de paqueraTrabalho Estudo Ativismo Lazer Grupos de apoio Se informar Conhecer gente nova Conectar com a família Flertes/relacionamentoRacismo LGBTfobia Preconceito de classe social Machismo Intolerância religiosa Xingamentos e/ou humilhações Vazaram meus nudes Ameaças psicológicas e/ou de violência física Expuseram minha orientação sexual e identidade de gênero sem meu consentimento Assédio sexualPost removido Conta bloqueada/excluída Conta invadida (ex. alguém entrou no meu perfil fingindo que era eu) Conta roubada (ex. nao consegui mais ter acesso) Tive problemas com verificação de identidade (ex. pediram meu documento e ele nao bate com meu nome social)Sim, antes e durante a pandemiaNaNNaNSimNãoQuase nunca vouQuase nunca vouNãoSim, leio com frequência a livros, revistas digitais e/ou artigos onlineExtremamente importanteNão, os ingressos para esses eventos são carosNaNA maioria dos eventos que acesso são promovidos por organizações civisNão, acredito que não existaNão conheço nenhumNão seiArtes visuais (pintura, escultura, etc) Música (cantor, produtor, instrumentista, etc) Teatro Fotografia Literatura/escritaNaN